Sökresultat för "Mathematical Optimization"

Adyen

This is Adyen Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition.  For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. Senior AI Engineer We are looking for a Senior AI Engineer to join our AML (Anti-Money Laundering) Tech team in Amsterdam. You will help build our next-generation financial crime investigation system, leveraging AI to manage and mitigate risk at scale. With our global footprint, you will have access to a uniquely rich dataset to fuel these solutions. You will bridge the gap between applied research and engineering excellence, taking ownership of the end-to-end lifecycle of these AI systems – from initial ideation to production. We are building a Human-in-the-Loop system. By evolving our capabilities from isolated workflows to a highly performant, trustworthy agentic system, you will shape how humans and AI collaborate in a complex, regulated domain. This is a unique opportunity to be part of the foundational group driving AI product development at Adyen. You will be building zero-to-one products, setting the architectural standards for our team, and defining how AI is practically deployed across the company. In this role, you will: * Build Agentic Systems: You will lead the design and deployment of robust, multi-step AI agents tailored for complex investigation workflows (orchestration, tool dispatching, state and memory management, error recovery, human-in-the-loop design). * Develop Platform Infrastructure: You will build a scalable modular agent platform that seamlessly integrates with enterprise data to support Adyen’s massive operational scale and diverse use cases. * Architect Evaluation Frameworks: You will design custom, domain-specific benchmarks and reusable infrastructure to rigorously test LLM reliability, edge cases, failure modes, and overall production readiness. * Provide Strategic Leadership: You will act as the leading engineer for the team, driving the AI product roadmap in close collaboration with a high-performing product team and leadership, guide company-wide MLOps decisions, evaluate third-party tools, and lead cross-functional integration. Who You Are: * Experienced Builder: 5+ years in Software or Machine Learning Engineering, including 2+ years successfully designing and productionizing AI systems. * Agentic Architecture Expert: Proven experience in applied AI, with a focus on building systems around pre-trained models (e.g., context engineering, fine-tuning, RAG, inference optimization, orchestrating model interactions with external tools to deliver solutions, multi-step tasks). You know exactly what separates a research prototype from a production agent. * Engineering & MLOps Pragmatist: Highly proficient in Python with a strong grasp of engineering best practices and tracking "LLM-native" metrics (e.g., granular tracing, tokens/sec, cost-per-request). * Proactive Leader: A self-starter who thrives in ambiguity, continuously raises the technical bar, influences system architecture, and mentors the team to build for scale. * Educated: Master’s degree in a STEM field (Science, Technology, Engineering, Mathematics) or equivalent technical background. * Bonus (Nice to Have): A strong foundation in traditional Machine Learning. You understand that this product sits within a broader ML ecosystem and pragmatically choose the right tool for the problem. Our Diversity, Equity and Inclusion commitments  Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them - voices like yours. No matter who you are or where you’re from, we welcome you to be your true self at Adyen.  Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application! What’s next? Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don’t be afraid to let us know if you need more flexibility. This role is based out of our Amsterdam office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.

ABB AB

At ABB, we help industries run leaner and cleaner—and every person here makes that happen. You’ll be empowered to lead, supported to grow, and proud of the impact we create together. Join us and help run what runs the world. This position reports to: R&D Team Lead__ Your Role and Responsibilities Are you ready to take the next step in your R&D career and help drive innovation within one of the world’s leading technology companies? As R&D Scientist, you will become a part of the Power Electronics & Applications team at ABB Corporate Research in Västerås, Sweden. ABB's Corporate Research serves as the innovation engine, ensuring our technological leadership both now and in the future. We work closely with other research centers, business areas (Motion, Automation, Electrification), and academic and industrial partners. Within our creative and highly skilled team, we design, build, and validate novel concepts and prototypes for both physical and digital systems. Our work covers the entire chain, including electric energy sources, grid-connected converters, electric motors and drives. As part of this role, you’ll report to the R&D Team Manager, actively collaborating on and driving the execution of exciting R&D projects. To thrive in this position, a positive and structured mindset, a solid technical background, and genuine enthusiasm for leveraging our highly advanced simulation and experimental facilities are essential. This regular employment opportunity serves as an excellent starting point for an engaging career within ABB. Key Responsibilities Lead and drive R&D initiatives from idea to validated concept, including defining scope, collaborating with key stakeholders, and sharing results. Develop and validate innovative solutions in applied power electronics, through high-fidelity modeling of power electronics and control strategies, as well as hands-on design and construction of experimental test setups in our laboratories. Explore and challenge conventional approaches, scouting new technologies and concepts while contributing to the development of digital solutions for ABB’s future portfolio. Our Team Dynamics Our teams support each other, collaborate, and never stop learning. Everyone brings something unique, and together we push ideas forward to solve real problems. Being part of our team means your work matters - because the progress we make here creates real impact out there. Qualifications for the role PhD in power electronics, electrical engineering, applied mathematics, or an MSc combined with substantial relevant industry or research experience, with a strong theoretical foundation and hands-on expertise in power electronics topologies, control, and applications (e.g., grid-connected converters, energy storage, Electric motor drives). Proficiency in the design, modeling, simulation, and optimization of power converters and drives, including experience in condition monitoring and diagnostics of the systems. Strong experimental and analytical skills, with proven ability to design and implement test setups, plan and conduct experiments, analyze results, and clearly document findings. Knowledge of data-driven methods, machine learning, and advanced modeling techniques is considered a strong plus, especially for applications in predictive modeling, condition monitoring, and the optimization of systems. A collaborative and results-driven mindset, enabling effective cooperation across R&D teams and business stakeholders, combined with the initiative and leadership needed to deliver high-quality results on time and within budget. What’s in it for you? We empower you to take initiative, challenge ideas, and lead with confidence. You’ll grow through meaningful work, continuous learning, and support that’s tailored to your goals. Every idea you share and every action you take contributes to something bigger. ABB provides competitive benefits, ask us! More about us  Recruiting Manager Omer Ikram ul Haq, +46 (73) 066 06 22, will answer your questions about the position. Union representatives – Sveriges Ingenjörer: Carl-Fredrik Lindberg, +46 70 691 10 80; Unionen: Katja Saari, +46 730 77 05 02; Ledarna: Lenny Larsson, +46 706 32 85 47. All other questions can be directed to Talent Partner Robert Noren, +46 72 461 20 95. We look forward to reading your application in PDF format. Last day to apply is August 10. Please note that the interview process is ongoing, apply now to secure your spot in the recruitment process! Please note that to be eligible for employment at ABB Sweden, you will need to pass our pre-employment screening steps. This includes a reference check, a drug test, and could also include an extended background check. Building a cleaner, smarter future takes all kinds of minds: the curious, the courageous, and the creative. That's why we welcome people from all backgrounds and experiences. Ready to make an impact? Apply today or visit https://www.abb.com to learn more about the impact of our solutions across the globe.

ERICSSON AB

Company description: Ericsson AB Job description: Join our Team About this opportunityWe are looking for a passionate Digital Algorithm Developer to join our cutting-edge Algorithms team in Lund. In this role, you will contribute to the development of current and next-generation radio solutions by designing advanced algorithms and bringing them to life through efficient hardware implementations. If you are a recent graduate with a strong technical foundation, eager to learn and solve real-world engineering problems, and excited about applying theory to practice in a collaborative team, this is a great opportunity. You’ll thrive here if you enjoy working in teams, are proactive, and want to grow by working at the intersection of signal processing, hardware design, and emerging AI/ML techniques for real-time communication systems. You’ll be part of a highly collaborative and agile environment working across global teams, where innovation, ownership, and continuous learning are encouraged. What you will do•    Contribute to early studies and concept development for current and future radio solutions. •    Design, develop, and optimize digital signal processing (DSP) algorithms. •    Build and maintain behavioural models and simulation frameworks. •    Support development of end-to-end system simulations to evaluate algorithm performance under real-world conditions. •    Build and configure integrated lab setups, combining hardware and software components. •    Execute performance evaluations, measurements, and validation activities. •    Collaborate with cross-functional teams across algorithm, ASIC/FPGA, and system domains.The skills you bring•    MS in Electrical Engineering, Mathematics, Signal Processing, System on Chip, Artificial Intelligence/Machine Learning or related field. •    Solid grounding in the field of Mathematics, optimization, statistics, or adaptive algorithms. •    Good knowledge of Digital Signal Processing concepts and implementation techniques. •    Knowledge of algorithm design, simulator building and behavioural modelling languages such as Matlab, Simulink, Python, or C/C++. •    Understanding of ASIC/FPGA design flows and hardware-aware algorithm design. •    Experience in RTL implementation of designed algorithms and HDL languages such as VHDL, Verilog or System Verilog. •    Knowledge of Artificial Intelligence/Machine Learning. •    Knowledge of telecommunication systems and RF (radio frequency) fundamentals. •    Experience working with lab equipment, including signal analysers, signal generators, and power supplies. •    Additional experience with AI/ML techniques applied to signal processing or communications, High-Level Synthesis (HLS) tools, digital/analog/mixed-signal IC design, and power amplifier technologies or FPGA prototyping platforms is a plus but not required.

Stripe

WHO WE ARE ABOUT STRIPE Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. ABOUT THE TEAM Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background. WHAT YOU’LL DO We’re looking for a Data Scientist to partner with our Global Growth teams. You’ll play a key role in designing and shipping experiments, as well as identifying improvement opportunities across stripe.com and the dashboard to help businesses worldwide get started on Stripe. You’ll help us understand, grow, and optimize the self-serve user funnel to ensure a consistently high-quality onboarding experience for users globally. As Data Scientists at Stripe, our mission is to ensure that company strategy, products, and user interactions make smart use of our rich data using techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics. WHO YOU ARE We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. MINIMUM REQUIREMENTS * Bachelors + 8 years or Masters + 6 years or Phd + 3 years of data science or quantitative modeling experience * Proficiency in SQL and a computing language such as Python or R * Experience in working with cross-functional teams to deliver results * Ability to communicate results clearly and a focus on driving impact * A demonstrated ability to manage and deliver on multiple projects with a high attention to detail * Strong business acumen and experience in synthesizing complex analyses into actionable recommendations * Proficiency with AI tools to accelerate model development, analysis, and coding PREFERRED QUALIFICATIONS * Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and experimentation * Experience deploying models in production and adjusting model thresholds to improve performance * Experience designing, running, and analyzing complex experiments or leveraging causal inference designs * A builder's mindset with a willingness to question assumptions and conventional wisdom * Experience with distributed tools such as Spark, Hadoop, etc. * A PhD or MSc in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)

Datadog

The Behavior AI team builds the AI-based anomaly detection behind Datadog's security products. Our models learn what normal looks like across the billions of logs, events, and telemetry records flowing through the platform every second, and they flag the behavior that does not fit, on every record, in real time, at a cost that makes sense at our scale. What we build does not ship to a single feature. The same models power detection across many of Datadog's security products at once, so the work has impact well beyond any one team. Large general-purpose models are too slow and too expensive to run in that path, so we take the opposite approach: small, custom models, designed for high-throughput stream processing and optimized to run cheaply on every record.   We are hiring a Senior Applied Scientist to build these models from start to finish. You will contribute to designing the architecture, training at scale, and the optimization work that takes a model from training to running efficiently on production traffic. This optimization requires a deep understanding of the constraints imposed by both the software and the hardware, together with the applied mathematics to work within them: often it comes down to finding a mathematical reformulation that fits those constraints better, and that judgment can decide whether a model reaches production at all.   The work involves a number of open questions. How do you obtain most of the quality of a large model from one that is far smaller and cheap enough to run on the full stream? Where is it worth trading exactness for speed, and how do you reason about the error you accept? How do you make a small model's outputs clear enough that the detection engineers and analysts who rely on it can trust what it reports? If these are the problems you want to work on, we would like to hear from you.   At Datadog, we place value in our office culture: the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.   What You'll Do:   * Design and build custom mid-size models for high-throughput stream processing, and train them at scale.   * Optimize these models from start to finish, working across both the mathematics and the systems, often by finding mathematical reformulations that fit the hardware and software constraints better.   * Build the training data pipelines the work depends on when they do not already exist, from the raw stream to a training-ready dataset.   * Work with engineering to integrate models into production, with a clear focus on GPU utilization, latency, and cost per record on live traffic.   * Plan the roadmap of model and system improvements, based on a solid understanding of the product and of what matters most to users.   * Build an agentic layer on top of the models to analyze, validate, and act on their outputs.   * Build lightweight interpretability tools that make model behavior easier to explain to the people who rely on it.   * Maintain and monitor the models, services, and infrastructure your team owns, and take part in your team's on-call rotation.   Who You Are:   * You have a BS/MS/PhD in Computer Science, Engineering, Machine Learning, Applied Mathematics, or a related scientific field, or equivalent experience.   * You have hands-on experience training and fine-tuning models at scale, and deploying them into production systems with real throughput and cost constraints.   * You have a working knowledge of how GPUs work, and a track record of making models run efficiently within real hardware constraints.   * You have strong applied-mathematics fundamentals and reach for them naturally when designing and optimizing models.   * You have a real passion for applied mathematics, software design, and implementation. This role sits at the intersection of the three, and it is a requirement for the position.   * You care about code simplicity and performance, and you can build the data pipelines and the surrounding production code, in addition to the models themselves.   * You can explain complex ideas and trade-offs clearly to engineers and product partners, and you let a solid understanding of the product guide what you build next.   * Bonus: experience with efficient sequence architectures, model interpretability, or large-scale streaming systems.   Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you're passionate about technology and want to grow your skills, we encourage you to apply.   Benefits and Growth:   * New hire stock equity (RSUs) and employee stock purchase plan (ESPP) * Continuous professional development, product training, and career pathing * Opportunity to attend and present at conferences and meetups, and to publish your work * Intra-departmental mentor and buddy program for in-house networking * An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups) * Competitive global benefits   Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.   About Datadog, Equal Opportunity, and Privacy and AI Guidelines boilerplate is appended automatically by the applicant tracking system. Add Datadog's current standard blocks before publishing.   #LI-Hybrid ---------------------------------------------------------------------------------------------------------------------------------- About Datadog:  Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center. ---------------------------------------------------------------------------------------------------------------------------------- Equal Opportunity at Datadog: Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.  Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications.  Privacy and AI Guidelines: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.

RISE Research Institutes of Sweden AB

AI is developing fast – far beyond the speed of traditional technological evolution, and energy systems are becoming ever more complex, distributed and interconnected. Do you, just like us, want to help build the intelligent, data-driven tools that will keep tomorrow’s energy systems reliable and resilient? We are looking for a motivated PhD student who wants to develop AI methods and digital twins for resilient energy systems, with a focus on district heating and cooling and building energy systems. You will combine machine learning, modelling and simulation to better understand, predict and strengthen these systems under uncertainty and disturbance – working at the intersection of AI, digital twins and the built environment. About us At RISE, the unit Connected Intelligence conducts applied research and development at the meeting point between artificial intelligence, connected systems and the physical world. We build intelligent, data-driven solutions that turn sensor data, models and real-time information into decisions – for industry, public agencies and society. Our team is interdisciplinary and hands-on. We are a group of researchers who develop practical, trustworthy AI solutions together with industry partners, public agencies and academia. As a PhD student you will be employed at RISE and enrolled as a doctoral student at KTH Royal Institute of Technology, with an academic supervisor at KTH in addition to your supervisors at RISE. About the role In this position you will pursue doctoral research on AI and digital twins for resilient energy systems, with a focus on district heating and cooling networks and building energy systems. The overall direction is set, while the specific scientific contributions will be shaped together with you. You will: Develop AI and machine-learning methods for modelling, monitoring and forecasting in district heating and cooling networks and building energy systems Build and validate digital twins that mirror the behaviour of these energy systems and their assets in real time Investigate how data-driven methods can improve the resilience and efficiency of district heating/cooling and building energy systems against faults, disturbances and changing conditions Combine physics-based models with data-driven approaches (e.g. hybrid and physics-informed machine learning) Validate methods on real data and in relevant testbed or simulation environments together with energy utilities, property owners and research partners Publish your results in leading international conferences and journals, and present them in research and industry forums Contribute to research and innovation projects within the unit The position is a full-time, time-limited doctoral employment, normally up to five years including approximately 20% departmental work, leading to a PhD. The role is based in Kista, Stockholm, and you are expected to spend 3 days per week in KTH, Campus Valhallavägen for coursework, research collaboration, and possibly teaching duties. Because some projects may be security-sensitive, a security clearance may be required now or in the future. Who are you? Required qualifications: A Master’s degree (or equivalent) in computer science, electrical or energy engineering, applied mathematics, physics or a closely related field Solid foundation in machine learning and/or modelling and simulation Good programming skills (e.g. Python) A strong interest in energy systems – especially district heating/cooling and building energy systems – and in digital twins Ability to work independently as well as in a team Excellent communication skills in English, written and spoken Meriting qualifications: Experience with deep learning and modern AI frameworks (e.g. PyTorch, TensorFlow) Strong knowledge of energy systems, especially district heating/cooling and building energy systems, combined with strong modelling and simulation skills Experience with digital twins, simulation or physics-informed/hybrid modelling Experience working with time-series data, sensor data or real-time systems Experience with optimisation, control or uncertainty quantification Prior research experience or scientific publications Good communication skills in Swedish Personal qualities: A strong technical interest and a desire to work at the forefront of technology Curiosity and a drive to learn, explore and solve complex problems Strong analytical skills Communicative and able to collaborate with both technical and non-technical stakeholders Proactive, with the ability to take initiative and see the bigger picture in complex systems Are we a good match? We work across the entire AI pipeline – from data collection and communication to modelling, learning and decision-making – with a focus on trustworthiness, robustness and real-world impact. Resilient and efficient district heating/cooling and building energy systems are a strategic societal challenge for the energy transition, and digital twins powered by AI are one of the most promising tools to address it. As a PhD student at RISE you will have: The opportunity to do impactful research on a strategically important societal challenge Access to real data, testbeds and simulation environments together with leading partners Close collaboration with experienced researchers and industry partners A combination of applied research and academic training, leading to a PhD A flexible, supportive and research-driven work environment

Avaron AB

About the Company At Avaron, you get the security of permanent employment combined with the variety of working at different customers. We place specialists across everything from tech, IT and industry to project management and business support – and whatever the assignment, you have a consultant manager who is there for you and your development. About the Role You will join an agile team building AI-powered analytics solutions for intelligent connected devices. In this role, you will help create computer vision applications that need to perform reliably in varied real-world environments and use cases. You will work across the full product lifecycle and contribute to solutions where software quality, performance, and robustness matter. This is an exciting opportunity if you want to combine AI, computer vision, and software engineering in a product-focused environment. Job DescriptionYou will develop and maintain computer vision and AI-based software applications. You will design and implement software for Linux-based embedded systems using C++ and Python. You will improve algorithms with a focus on accuracy, robustness, and performance. You will take part in the full software development lifecycle, from design and implementation to testing, validation, and maintenance. You will use a data-driven approach to analyze results and continuously improve solution quality. You will collaborate closely with software developers, AI engineers, and other specialists in cross-functional teams. You will contribute to the development of next-generation AI-powered products. RequirementsMaster's degree in Computer Science, Engineering Physics, Mathematics, or a related field. Experience with, or a strong interest in, Computer Vision, AI, or Machine Learning. Programming experience in C++, Python, and Linux environments. A strong interest in software engineering, algorithm development, and complex technical problem-solving. The ability to work well with others in a collaborative development environment. Nice to haveExperience with data-driven algorithm development. Experience with Machine Learning or AI-based product development. Experience with embedded software development. Experience with performance optimization and software validation. What We OfferPermanent employment at Avaron AB Occupational pension Wellness allowance of SEK 5,000 per year Application Selections are made on an ongoing basis – apply as soon as you can.

CHALMERS TEKNISKA HÖGSKOLA AKTIEBOLAG

We are seeking an ambitious applied researcher who wants to work at the forefront of data-driven nutrition and health. This is a unique opportunity to bridge mathematics, statistics, AI, and biomedical research in a highly interdisciplinary research environment. About us Fraunhofer-Chalmers Centre (FCC) is a leading research centre in industrial mathematics, modelling, simulation, optimisation, and data analytics. We operate at the interface between academic research and industrial needs, often in interdisciplinary projects where mathematics, data, and domain expertise meet. Together with the nutrition research group led by Professor Rikard Landberg at Chalmers University of Technology, we conduct advanced research in data-driven nutrition, health, and food science. With large-scale diet and health data, omics data, biomarkers, digital food and health services, we establish predictive models for evaluation of the role of diet in health and disease and establish personalized dietary strategies for more effective disease prevention. In many cases, the work involves time series data, dynamic processes and phenomena, where both methods and interpretation must account for temporal dynamics. Data typically comes from intervention studies conducted in Gothenburg and or from large cohorts and biobanks from international collaborators. To secure and further develop this important collaboration, we are now recruiting an applied researcher with a strong quantitative profile and interest in nutrition, health, or medicine. Your role As an applied researcher in this area, you will: Act as a key person in the collaboration between FCC and the nutrition research group at Chalmers. Lead and conduct research projects in data-driven nutrition, such as:analysis of time series data and dynamic processes, where signals and responses evolve over time. statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome, etc.) development of predictive dynamical models and digital decision-support tools for nutrition and health method development in causal inference, integration of heterogeneous data sources, uncertainty quantification Work with a wide range of data types, for example dietary records, biomarkers, omics data, registry data, and sensor data such as CGM measurements (continuous glucose monitoring), activity trackers, and other wearable sensors. Serve as a bridge between domain researchers (nutrition, medicine, food science) and quantitative experts (mathematics, statistics, AI&ML, systems engineering). Supervise, collaborate, and support PhD students and postdocs involved in joint projects. Your profile We are looking for someone who: Holds a PhD in Applied Mathematics, Mathematical Statistics, Automatic Control, Signal Processing, Systems Engineering, Data Science, or a related field. Has experience in data-driven research, preferably related to biomedicine, nutrition, epidemiology, food science, or public health. Is proficient in modern statistical modelling, AI & machine learning methods (e.g. system identification, regression models, mixed-effects modeling, Bayesian methods, deep learning, variational autoencoders, generative AI). Is an experienced programmer in R and/or Python, and used to working with large datasets and reproducible analysis workflows. Enjoys working in interdisciplinary environments and is curious about understanding biological/nutritional research questions in depth. It is meritorious if you also: Have experience working with cohort data, registry data, clinical studies, or omics data. Have previously worked in projects involving both academic and industrial/external partners. Have experience supervising PhD students, postdocs, or junior researchers. Can communicate in both Swedish and English; excellent English is required. What we offer With us, you will: Have a unique opportunity to combine advanced quantitative and data-driven methods with cutting-edge research in biomedicine, nutrition, and health. Work in a strong and long-term collaboration between Fraunhofer-Chalmers Centre and Chalmers division of Food and Nutrition Science, with access to both international academic and industrial networks. Influence the direction of a strategically important initiative in data-driven nutrition and health. Be part of a creative, collaborative, and international research environment with good opportunities for personal and scientific development. Employer: Fraunhofer-Chalmers Research Centre for Industrial Mathematics (Fraunhofer-Chalmers Centre, FCC)   Employment: according to agreement   Location: Gothenburg, Sweden   Department: Systems and Data Analysis (in close collaboration with Chalmers)   Application procedure The application should be written in English and attached as PDF-files, containing as specified below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files.  - CV  - Publication list - Transcript of grades - Personal letter with: A brief description of your research profile and how it relates to nutrition/health A brief motivation as to why you are interested in this position.  Please apply no later than 16th August 2026. Evaluation of applications will be done on a continuous basis. Please note: The applicant is responsible for ensuring that the application is complete. Incomplete applications and applications sent by email will not be considered. Contact details to references will be requested after the interview.  For questions, please contact:   Mats Jirstrand, Head of Department, Systems and Data Analysis, Fraunhofer-Chalmers Centre E-mail: mats.jirstrand@fcc.chalmers.se Phone: +46 730 794303

Stripe

WHO WE ARE ABOUT STRIPE Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. ABOUT THE TEAM Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background. WHAT YOU'LL DO We're looking for a variety of Data Scientists to partner with the Product, Finance, Payments, Security, Risk, Growth, and Go-to-Market teams. You'll work closely with a specific part of the business, playing a crucial role in optimizing our systems and leveraging data to make strategic business decisions. As Data Scientists at Stripe, it's our mission to ensure that the company strategy, products, and user interactions make smart use of our rich data, using techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics. WHO YOU ARE We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. MINIMUM REQUIREMENTS * PhD with 3 years, MS or MA with 6 years, or BS or BA with 8 years of data science or quantitative modeling experience * Proficiency in SQL and a computing language such as Python or R * Experience in working with cross-functional teams to deliver results * Ability to communicate results clearly and a focus on driving impact * A demonstrated ability to manage and deliver on multiple projects with a high attention to detail * Strong business acumen and experience in synthesizing complex analyses into actionable recommendations * Proficiency with AI tools to accelerate model development, analysis, and coding PREFERRED QUALIFICATIONS * Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and experimentation * Experience deploying models in production and adjusting model thresholds to improve performance * Experience designing, running, and analyzing complex experiments or leveraging causal inference designs * A builder's mindset with a willingness to question assumptions and conventional wisdom * Experience with distributed tools such as Spark, Hadoop, etc. * A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)

Stripe

WHO WE ARE ABOUT STRIPE Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. ABOUT THE TEAM Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background. WHAT YOU’LL DO We’re looking for a Data Scientist to partner with our Local Payment Methods (LPM) engineering and product teams. You’ll play a key role in understanding, growing, and optimising our LPM business, leveraging data to make strategic business decisions. As Data Scientists at Stripe, it's our mission to ensure that the company strategy, products, and user interactions make smart use of our rich data, using techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics. WHO YOU ARE We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. MINIMUM REQUIREMENTS * PhD, MSc or MA with 2 years, or BS or BA with 3 years of data science or quantitative modeling experience * Proficiency in SQL and a computing language such as Python or R * Experience in working with cross-functional teams to deliver results * Ability to communicate results clearly and a focus on driving impact * A demonstrated ability to manage and deliver on multiple projects with a high attention to detail * Strong business acumen and experience in synthesizing complex analyses into actionable recommendations * Proficiency with AI tools to accelerate model development, analysis, and coding PREFERRED QUALIFICATIONS * Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and experimentation * Experience deploying models in production and adjusting model thresholds to improve performance * Experience designing, running, and analyzing complex experiments or leveraging causal inference designs * A builder's mindset with a willingness to question assumptions and conventional wisdom * Experience with distributed tools such as Spark, Hadoop, etc. * A PhD or MSc in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)

Ytsab Defence AB

Role Overview We are seeking a highly skilled and visionary Senior R&D Engineer (Electromagnetic Propulsion) to lead the physical modelling, simulation, and experimental validation of a next-generation, multistage Electromagnetic Launch System. In this role, you will bridge the gap between advanced physics theory and cutting-edge engineering. You will be responsible for defining the mathematical framework of inductance acceleration, optimizing pulsed-power efficiency, managing extreme thermal/mechanical stresses, and building physical prototypes to validate your models. If you thrive on solving highly complex, multi-physics problems and want to shape the future of high- velocity propulsion tech, this is your next challenge. Core Responsibilities 1. Physics Modelling & Electromagnetic Analysis  Develop the fundamental mathematical frameworks and multi-physics models (electromagnetic, thermal, and material physics) to describe inductance acceleration and transient system behaviours.  Investigate complex magnetic Lorentz forces, skin effects, and proximity effects acting on coils under high-frequency, time-varying currents.  Utilize advanced simulation tools to analyse a large parameter space (coil geometry, shape, size, and turn count) to optimize magnetic field production and projectile acceleration. 2. Multistage System Architecture & Optimization  Design and analyse multistage acceleration configurations, defining the optimal number of stages, mutual stage interactions, and microsecond-level activation timing architectures.  Optimize the stored-to-kinetic energy conversion efficiency by minimizing un-utilized magnetic flux, ohmic/resistive losses, and eddy current heating.  Define the boundary conditions, switching requirements, pulse shapes, and power regulation dependencies for the electrical and control subsystems. 3. Component Design & System Integration  Collaborate with external project partners to integrate custom-engineered, high-current pulsed-power coils optimized for mechanical stability and thermal resilience.  Oversee the concept design of specialized payloads to ensure seamless compatibility with the electromagnetic launch environment.  Address system-level integration challenges arising from high-intensity electromagnetic fields on surrounding components. 4. Thermal Management & Power Control  Identify transient heat sources within the accelerator stages and propose highly effective thermal management and cooling solutions.  Optimize the physical routing of the electrical power supply to the coil inductors to handle extreme stress environments. 5. Experimental Validation & Safety  Design, build, and operate an experimental test setup to validate simulation data, testing for acceleration efficiency, discharge pulse dynamics, and heat management.  Conduct comprehensive safety analyses on high-voltage and high-energy electromagnetic components.  Establish strict safety protocols and ensure total compliance with relevant electrical safety standards for pulsed-power operations. Required Technical Skills & Experience:  Education: Master’s or Ph.D. in Physics, Electrical Engineering, or a highly related field with a focus on Electromagnetics.  Simulation Mastery: Extensive experience with multi-physics simulation software (e.g., COMSOL, Altair Flux, or MATLAB/Simulink) focusing on transient electromagnetic fields.  Pulsed Power Expertise: Knowledge of inductance acceleration, magnetic forces, high-current switching, and power electronics.  Thermal & Mechanical Insight: Familiarity with managing thermal dissipation and mechanical stress in high-energy electrical systems.  Hands-on Testing: Experience setting up laboratory diagnostics, high-speed data acquisition systems, and working safely with high-voltage hardware. Preferred Attributes:  Experience in advanced aerospace or defence R&D, specifically in coil gun, or linear induction motor technologies.  Strong collaborative skills for working alongside external manufacturing and project partners.  A meticulous approach to safety protocols and risk analysis. What We Offer  Cutting-Edge Projects: Work on a disruptive, first-of-its-kind electromagnetic technology program.  Collaborative Culture: Join a highly collaborative environment alongside leading industry partners and academic experts.  Competitive Compensation: Attractive salary and continuous professional development paths. Due to the nature of this project, applicants must be eligible to obtain the required national security clearances. Öppen för alla Vi fokuserar på din kompetens, inte dina övriga förutsättningar. Vi är öppna för att anpassa rollen eller arbetsplatsen efter dina behov.

CHALMERS TEKNISKA HÖGSKOLA AKTIEBOLAG

Would you like to be part of designing next generation mobile communications system? Please consider to apply for our open Postdoc position in 6G radio digital twin (RDT)-assisted situation-aware integrated sensing and communications (ISAC) in distributed multiple-input multiple output (D-MIMO) systems for resilient and efficient intelligent transport systems (ITS) and 6G-integrated non-terrestrial networks (6G-NTN)! Chalmers University of Technology is located in Gothenburg on the scenic west coast of Sweden. It is among the top research schools in Europe. The research environment is international and English is the working language. Chalmers has a long tradition of international research in wireless communications in close collaboration with top international academia as well as both local and international telecommunications and automotive industry. A large part of such research is performed at the Department of Electrical Engineering (E2), where this post-doctoral position is announced. E2 is engaged in both fundamental and applied research, spanning a large variety of research areas including Automatic Control, Automation, Mechatronics, Biomedical Engineering, Communication Systems and Information Theory, Signal Processing and Antennas. Cross-disciplinary research is central and encouraged through projects across different groups within the Department. About us  At the https://www.chalmers.se/en/departments/e2/ (E2) research and education are performed in the areas of Communications, Antennas and Optical Networks, Systems and Control, Signal processing and Biomedical engineering, and Electric Power Engineering. We work with sustainable and smart solutions to societal challenges, such as energy efficiency and electrification in areas ranging from transport and production systems to communication solutions and biomedical engineering. https://www.chalmers.se/en/departments/e2/research/communications-antennas-and-optical-networks/ (CAOS) conducts research and education in wireless and optical technologies for communication and sensing. Combining fundamental and applied research, we address challenges in sustainability, security, and next-generation communication systems. The division also plays a key role in engineering education, particularly within the Master's programme in Information and Communication Technology. The https://www.chalmers.se/en/departments/e2/research/communications-antennas-and-optical-networks/communication-systems/employs around 45 people, including 9 faculty and 25 PhD students, and is active in a wide range of topics in digital communication. These include 6G wireless systems, hardware-constrained communication, localization and sensing, vehicular communications, fiber-optical communication, and distributed information systems. The Wireless Systems team within the Communication Systems Group has a long and strong track record on 4G, 5G and 6G and Beyond mobile communications systems with currently 4 PhD students and 2 Postdocs. About the research project   In this research environment, a postdoctoral researcher will be recruited within the Wireless Systems team to perform world-class research on 6G RDT-assisted situation-aware ISAC D-MIMO systems for resilient and efficient ITS and 6G-NTN. You will participate in interdisciplinary national and international research projects on 6G wireless systems with a special focus on proactive beamforming and resource allocation.  In particular, you will be active within our new Chalmers Area of Advance Transport project https://research.chalmers.se/en/project/12938, and in our ongoing Swedish Research Council (VR) Research Environment https://research.chalmers.se/en/project/12006. The appointment offers great opportunities to qualify for further research positions within academia or industry as we have numerous ongoing collaborations with the leading academic groups and industry both nationally and internationally, such as the EU Horizon Europe 6G-IA projects https://robust-6g.eu/and https://www.eco-enet.eu/, and within our research center https://www.chalmers.se/en/centres/witech/ at Chalmers, in particular within the project “Distributed communication and radar sensing convergence” (DisCouRSe). Who we are looking for  The following requirements are mandatory:  A doctoral degree in Electrical Engineering, Engineering Physics, Applied Mathematics, Computer Science,   Communication or an equivalent foreign degree. This eligibility requirement must be met no later than the time the employment decision is made Strong skills in mathematical analysis are essential, particularly communication theory, statistical signal processing, and optimization   techniques Strong skills in simulation techniques Strong written and verbal communication skills in English Excellent presentation and collaborative skills Strong interest in interdisciplinary work with researchers and engineers from other fields Previous first-author publication experience in IEEE journals You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research and education.  The following experience will strengthen your application:  Knowledge in cooperative communications, distributed MIMO, integrated sending and communications (ISAC), reconfigurable intelligent surfaces (RISs), cell-free Massive MIMO at mm-wave and (sub-)THz are highly advantageous Knowledge in non-terrestrial networks (NTN), in particular low Earth orbit (LEO) satellites and high altitude platform stattions (HAPS) are highly advantageous Knowledge in digital twinning is highly advantageous Knowledge in machine learning is highly advantageous Knowledge in mobile communications systems, resource allocation, and backhauling/fronthauling, both wireless and fiber-optical are advantageous Knowledge about hardware components is advantageous Knowledge in wireless security is advantageous It is highly meritorious if the doctoral degree has been obtained within the last three years prior to the application deadline   Read more and apply here: https://www.chalmers.se/en/about-chalmers/work-with-us/vacancies/?rmpage=job&rmjob=14971&rmlang=UK

CHALMERS TEKNISKA HÖGSKOLA AKTIEBOLAG

Join us at the Division of Chemical Physics, Department of Physics and Astronomy, and contribute to the development of next-generation artificial intelligence methods for materials discovery and sustainable energy technologies. About us  The Division of Chemical Physics conducts internationally recognized research at the interface of physics, chemistry, materials science, and data science. Our research spans computational materials design, catalysis, energy materials, machine learning, and artificial intelligence. We offer a collaborative and international research environment with close interactions between faculty, postdoctoral researchers, PhD students, and external partners from academia and industry. The Department of Physics and Astronomy is one of the largest departments at Chalmers University of Technology, with broad activities ranging from fundamental physics to applied research addressing societal challenges in energy, sustainability, and digitalization. About the research project   The project aims to develop novel AI and machine-learning methods for accelerated materials discovery. The focus is on combining generative AI, active learning, first-principles simulations, and machine-learning potentials to identify new multicomponent optoelectronic materials for energy-conversion applications. The successful candidate will contribute to the development of an autonomous materials-discovery framework capable of navigating extremely large compositional spaces while simultaneously optimizing multiple target properties such as optical performance, stability, and sustainability. Who we are looking for  We seek a highly motivated and independent researcher with a strong interest in artificial intelligence, computational materials science, and scientific software development. Mandatory qualifications A doctoral degree in Physics, Materials Science, Chemistry, Chemical Engineering, Computer Science, Applied Mathematics, or a closely related field, or an equivalent foreign degree. The degree must be awarded no later than the time the employment decision is made. Strong written and verbal communication skills in English. Experience in machine learning, scientific computing, computational physics, computational chemistry, or related fields. Experience with Python programming and modern scientific software development. Ability to work independently while contributing effectively to collaborative research projects. Strong analytical and problem-solving skills. Good interpersonal skills and a demonstrated ability to collaborate in interdisciplinary teams. You are expected to have some experience with teaching or supervision and to demonstrate strong potential for future development in both research and education. Meritorious qualifications It is highly meritorious if the doctoral degree has been obtained within the last three years prior to the application deadline. Experience with machine learning for scientific applications. Experience with deep learning frameworks such as PyTorch or TensorFlow. Experience with atomistic simulations, density functional theory (DFT), molecular simulations, or machine-learning potentials. Experience with generative AI, active learning, uncertainty quantification, Bayesian optimization, or reinforcement learning. Experience with high-performance computing (HPC). Experience supervising students or junior researchers. What you will do  As a postdoctoral researcher, you will: Develop machine-learning and AI methods for materials discovery. Design and implement active-learning workflows for autonomous exploration of materials spaces. Develop and evaluate generative AI models for inverse materials design. Perform large-scale computational screening using first-principles calculations and machine-learning potentials. Analyze structure–property relationships and extract scientific insights from AI models. Publish research results in leading international journals and present findings at international conferences. Contribute to the development of open and reproducible scientific software. The position also includes: Supervision of master's students and, to some extent, PhD students. Opportunities to contribute to teaching at undergraduate and master's levels. Collaboration with national and international academic and industrial partners. Contract terms   The position is a temporary full-time employment for two years with the possibility of a one-year extension.  The position requires physical presence throughout the entire employment. A valid residence permit must be presented by the start date, otherwise the offer may be withdrawn.  What we offer  As a postdoc at Chalmers, you are an employee and enjoy all employee benefits. Read more about  working at Chalmers  and our benefits for employees.  A dynamic and inspiring working environment in the coastal city of Gothenburg.  Read more about Sweden’s generous parental leave, subsidized day care, free schools, healthcare etc at Move To Gothenburg.  Chalmers is dedicated to improving gender balance and actively works with equality projects, such as the GENIE Initiative for gender equality and excellence. We celebrate diversity and consider equality and inclusion as fundamental aspects of all our activities.  If Swedish is not your native language, Chalmers offers Swedish courses to help you settle in.  Application procedure  The application should be written in English be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files.  CV  A comprehensive CV, including a complete list of publications.  Details of previous teaching and pedagogical experience.  Personal letter  A brief introduction about yourself.  A summary of your previous research fields and key research outcomes.  An outline of your future goals and research focus.  Use the button at the foot of the page to reach the application form.       A background check may be conducted as part of the application process.     Please note: The applicant is responsible for ensuring that the application is complete. Incomplete applications and applications sent by email will not be considered. Contact details to references will be requested after the interview.    We welcome your application no later than 17 July  For questions please contact:  Anders Hellman Professor  anders.hellman@chalmers.se

SCANIA CV AKTIEBOLAG

TRATON is a group of strong brands with a shared mission: transforming transportation together to create the future of sustainable transport solutions. Within TRATON, we include MAN, Scania, Volkswagen Truck & Bus, and International. As part of a global team of industry experts, you get to think bigger, experience more, and reach further. Together, we have the power to transform transportation - Let's make a difference together. Find out more: www.traton.com Our values – customer first, respect, team spirit, responsibility, and elimination of waste – are at the heart of everything we do. Role Summary This role is a part of TRATON Group R&D, located in Södertälje, Sweden We are looking for a motivated candidate for the position of Industrial PhD Student in a joint research initiative between TRATON Group R&D and KTH. The doctoral work will be academically supervised by Professor Karl H. Johansson and Professor Jonas Mårtensson at KTH, in close collaboration with TRATON Group R&D. The project focuses on safety assurance for AI-based autonomous driving systems in heavy-duty vehicle applications. AI-based driving architectures can generate high-quality nominal driving behavior, but they also require independent safety mechanisms that ensure the executed motion remains safe, feasible, and predictable under uncertainty. The PhD project will investigate Guardrails and Verified Planning and Control methods for heavy-duty vehicles, with the aim of supporting near-term ADAS applications while building foundations for higher levels of automation. The work combines autonomous driving, control theory, optimization, machine learning, safety assurance, and heavy-duty vehicle engineering. Job Responsibilities Conduct doctoral research on safety assurance methods for AI-based autonomous driving systems. Develop and research methods that help ensure AI-generated driving behavior remains safe, feasible, and predictable for heavy-duty vehicles. Design, implement, and evaluate algorithms using simulation, scenario-based testing, and relevant industrial toolchains. Collaborate closely with researchers and engineers from TRATON Group R&D and KTH. Publish scientific results at leading conferences and in journals. Participate in doctoral courses, seminars, workshops, and the broader autonomous systems research community. Who You Are You hold a Master's degree in a relevant technical field, with strong mathematical foundations, proven programming skills, and a clear interest in autonomous systems, control, safety, and AI-based vehicle architectures. You are self-motivated and analytical, and able to work both independently and in teams. You enjoy applied research and are motivated by developing rigorous methods that can be evaluated in realistic industrial settings. You communicate complex ideas clearly and are fluent in English. Experience with several of the following is beneficial: Programming and software development in Python, C++, or MATLAB/Simulink. Machine learning, motion planning and control, optimization, or safety assurance methods. Vehicle modeling or modeling of complex systems. Autonomous vehicles, ADAS, or intelligent transportation systems. ROS or other robotics middleware. Scientific writing, peer-reviewed publications, or research project experience. We welcome applicants from all backgrounds – your unique experience and perspectives is valuable to us. This Is Us We are a 450-person department developing advanced driver assistance systems and Level 4 autonomous driving. About 100 specialists work on sensing technologies, while our 15-person unit focuses on software—from sensor fusion to controlling vehicle actions—building systems that improve safety and automation. Me as a manager As a manager, I focus on empowering people rather than using a top-down or directive approach. I prioritize team development and well-being, trusting that with the right support and growth opportunities, individuals will find their own ways to contribute, while stepping in only when needed. - Jon Andersson, Unit Head Within TRATON Group R&D, you are an important part of something bigger. Joining us means gaining access to the ins and outs of the entire transportation industry. TRATON Offers We offer a dynamic and engaging workplace where collaboration, innovation, and continuous improvement are part of everyday life. You will be part of a strong team environment that encourages knowledge sharing and close cooperation across functions. With a structured development plan and a wide range of training opportunities, TRATON Group R&D supports your professional growth both locally and internationally. Benefits include access to our health center in Gröndal or a wellness allowance, bonus, flexible working hours, and company car leasing. We also arrange events for employees and their families, and for those living in Stockholm, convenient commuting is supported through direct Scania Job express buses to Södertälje. Application We look forward to receiving your application, consisting of your CV and kindly ask you not to share a cover letter to ensure an efficient and unbiased recruitment process for all parties. Apply as soon as possible, no later than 2026-07-22. Screening will take place on an ongoing basis during the application period. Logical and personality tests may be used as part of the selection process, and a background check may be required for this role. If you have questions or would like more information, please contact: Jon Andersson, Unit Head, jon.andersson@scania.com. For technical questions about the project, please contact Pedro Lima at pedro.lima@scania.com We look forward to your application! This recruitment process is handled by Scania for TRATON Group R&D

LULEÅ TEKNISKA UNIVERSITET

Luleå University of Technology experiences rapid growth with world-leading expertise within several research areas. Our scientific and artistic research and education are conducted in close collaboration with international, national and regional companies, the public sector and leading universities. Luleå University of Technology has an annual turnover of just over SEK 2.3 billion. We have more than 1,800 employees and nearly 21,600 students. The Division of Materials Science at Luleå University of Technology invites motivated candidates interested in conducting research in Engineering Materials, with a focus on the design and development of advanced sorbent materials for environmental and gas-cleaning applications. The research subject "Engineering Materials" has ongoing research programs span broad research areas in metallic and ceramic materials (high-temperature intermetallic, space materials, high-strength steels, porous ceramic materials, and materials intended for energy recovery). The division is part of the Department of Engineering Science and Mathematics. The department has several other research topics with activities that border on material technology, such as materials mechanics and machine elements. In the undergraduate program, the main two programs focusing on the international profile of the Division of Materials Science are important for the department, namely the EEIGM master's engineering program and the AMASE master's program. Within these educations, many students perform project work and degree projects in projects related to our research. The research subject of Engineering Materials consists of seven senior researchers, two technicians, and eleven doctoral students.   SUBJECT DESCRIPTION Engineering materials includes the field of material composition, structure, properties and production of materials – mainly metallic and ceramic – as well as application aspects.   PROJECT DESCRIPTION The PhD student will focus on the synthesis, optimization, and characterization of advanced sorbent materials for selective NOx and SOx capture under humid industrial conditions. Based on computational design results provided by project partners, the student will develop functionalized activated carbons, ion-exchanged zeolites, and MOF-based hybrid composites with improved adsorption selectivity, moisture stability, and low-temperature regeneration capability. The work will include investigation of adsorption mechanisms, binding thermodynamics, NO and NO2 discrimination, and the effects of SO2 cross-interference using advanced characterization and adsorption testing techniques. The research will also address sorbent durability under realistic gas mixtures containing impurities, while optimizing material formulations for additive manufacturing compatibility and pilot-scale implementation. The project is approved for funding in EIC Pathfinder challenges from waste to value creation.   DUTIES Working as a researcher involves defining your daily tasks and how they will be carried out. You will act and train as a project manager, combined with your development. Involvement with other projects and teaching will occur up to 20 percent of your time.   QUALIFICATIONS Appropriate background for the position is a Master of Science degree in materials science, chemistry or chemical engineering, good knowledge, experience, on sorption and catalysts and their characterization. The candidate must be good at written and oral English. Experience in processing science, porous materials, and synthetic chemistry is advantageous.   INFORMATION Employment as a doctoral student is time-limited to 4 years, teaching and other department duties can add up to 20% of full-time. Place of employment is Luleå at the Department of Engineering Science and Mathematics, Division for Materials Science.   For further information please contact: Professor Farid Akhtar, +46 920-49 1793 mailto:farid.akhtar@ltu.se Professor Alberto Vomiero, +46 920-49 3139 mailto:alberto.vomiero@ltu.se   Union representatives: SACO-S Diana Chroneer, +46 920-49 2037 mailto:diana.chroneer@ltu.se OFR-S Marika Vesterberg, +46 920-49 1721 mailto:marika.vesterberg@ltu.se   Luleå University of Technology works actively with gender equality and diversity, contributing to a creative study and work environment. The university's values ​​are based on respect, openness, cooperation, trust and responsibility.   APPLICATION We prefer that you apply for this position by clicking on the apply button below. The application should include a CV, personal letter and copies of verified diplomas from high school and universities. Mark your application with the reference number below. Your application, including diplomas, must be written in English or Swedish. Closing date for applications: August 9, 2026 Reference number: 3877-2026

ÖREBRO UNIVERSITET

Örebro University and the School of Science and Technology are looking for a doctoral student for the doctoral programme in mathematics, concluding with a doctoral degree. Start date: Autumn semester 2026. Project description To invest in stocks or some other fluctuating commodity requires, in most cases, some mathematical model of risk, return (profit), or utility (some balance between risk and return). A classical model goes back to 1952 and Markowitz. Later, more advanced models go under the name Modern Portfolio Theory. Those models may be ill-posed, meaning that changes in data might result in very different investment strategies. One such example of ill-posedness is when some of the commodities are highly correlated. This project is about analyzing such ill-posed portfolio optimization and developing stable and efficient algorithms for solving them. Supervision: The doctoral student will be supervised by Professor Mårten Gulliksson (principal supervisor), Docent Magnus Ögren and Docent Stepan Mazur (assistant supervisors). The programme and the doctoral studentship The doctoral programme consists of courses and an independent research project that you will present in a doctoral thesis. The programme concludes with a doctoral degree and comprises 240 credits, which corresponds to four years of full-time study. The plan is that the doctoral student will be active with teaching duties corresponding to about 20% of the time, giving a total time of five years. Our ambition is for your doctoral studies to be stimulating and purposeful throughout the programme until you have obtained your doctoral degree. A thorough introduction will therefore get you off to a good start and provide a solid foundation on which you can build your studies. As a doctoral student at Örebro University, you will be offered a specially tailored seminar series, covering matters ranging from doctoral programme rules and careers to support during the study period and networking. The place on the programme is linked to a full-time doctoral studentship for the duration of the study programme, which corresponds to four years of full-time study. More information on doctoral studentships, part-time studies and part-time doctoral studentships can be found in the Regulations Handbook (https://www.oru.se/globalassets/oru-en/education/research-education/regelhandbok-for-utbildning-pa-forskarniva_en.pdf). The initial salary for a doctoral studentship is SEK 32,300 a month. Entry requirements and selection For admission to doctoral studies, applicants are required to meet both the general entry requirements (https://www.oru.se/english/study/doctoral-education/how-to-become-a-doctoral-student/) and specific entry requirements. In addition, applicants must be considered in other respects to have the ability required to benefit from the programme. For a full account of the entry requirements, refer to the admissions regulations (https://www.oru.se/globalassets/oru-en/education/research-education/application-and-admission/antagningsordning-for-utbildning-pa-forskarniva-vid-orebro-universitet_en.pdf) as well as to annex 2 to the general syllabus for mathematics (https://www.oru.se/globalassets/oru-en/education/research-education/general-syllabi/allman-studieplan-matematik_beslut_2024-06-13_en.pdf). To see the job advertisement and requirements in its entirety, visit: https://www.oru.se/english/career/available-positions/job/?jid=20260176  Information For more information about the programme and the doctoral studentship, contact Professor Mårten Gulliksson, email: mailto:marten.gulliksson@oru.se. At Örebro University, we expect each member of staff to be open to development and change; take responsibility for their work and performance; demonstrate a keen interest in collaboration and contribute to development; as well as to show respect for others by adopting a constructive and professional approach. Örebro University actively pursues equal opportunities and gender equality as well as a work environment characterised by openness, trust and respect. We value the qualities that diversity adds to our operations. Application to the programme and for the doctoral studentship The application is made online. Click the button “Apply” to begin the application procedure. For the application to be complete, the following electronic documents must be included: CV Copies of the original certificate and official transcript for Bachelor's degree Copies of the original certificate and official transcript for Master's degree Independent project (degree project) Other relevant documents, course and degree certificates verifying eligibility As a main rule, application documents and attachments are to be written in Swedish, Danish, Norwegian, or English. Certificates and documents in other languages verifying your qualifications and experience must be translated by an authorised translator to Swedish or English. A list of authorised translators can be obtained from Kammarkollegiet (the Legal, Financial and Administrative Services Agency), http://www.kammarkollegiet.se/engelska/start. When you apply for admission, you automatically also apply for a doctoral studentship. More information for applicants will be found on our career site: https://www.oru.se/english/career/available-positions/applicants-and-external-experts/ The application deadline is 2026-08-17. We look forward to receiving your application! As we have already made our choices in terms of external collaboration partners and marketing efforts for this recruitment process, we decline any contact with recruitment agencies and advertisers. As directed by the National Archives of Sweden (Riksarkivet), we are required to deposit one file copy of the application documents, excluding publications, for a period of two years after the appointment decision has gained legal force.