Learning & Development Lead

STIFTELSEN STOCKHOLM INTERNATIONAL SCHOOL

Reports to: Middle School Principal Our vision To be recognised as a leading international school that inspires and educates generations of global change-makers. Our mission Stockholm International School inspires and educates children of the global community through internationally recognised learning programs. We enable international mobility and support growth and talent development in the Stockholm region and beyond. Description/Purpose Middle School Teacher for Science grades 6 through 9. Duties/Responsibilities The teacher is responsible for the following: Teaching of Grades 6-9 Science. Contributing to the development and implementation of the Science curriculum. Communicating regularly with parents. Be an active and contributing member of the School’s faculty. Participating in the full range of professional activities in the school. Actively contributing to the operational needs of the school. Fulfilling other assigned roles such as advisory and duties. Required Qualifications, Education and Experience Qualifications in the area of Middle School Science. Bachelor's Degree or equivalent in Science. At least 3 years of teaching experience in Science. Preferred experience with IBMYP curriculum (Middle Years Programme). Preferred additional qualifications in other academic disciplines. Excellent communication skills. The ability to establish a positive rapport with adults and students. The ability to work effectively in a team. A pleasant and friendly personality. The ability to function effectively under pressure. The ability to show initiative and work independently. At Stockholm International School we are committed to protecting children. Aligned with the recommendations of the International Task Force on Child Protection, we hold ourselves to a high standard of effective recruiting practices with specific attention to child protection. All applicants will therefore be required to undergo appropriate child protection screening. Included in the recruitment process will be a local and national police check as well as a mandatory police background check from the last 10 years of employment in every country worked. A judicial background check will be conducted prior to the issuance of the contract for prospective candidates applying to work at our school. What we offer: As well as the exciting opportunities this role presents, we also offer benefits in terms of; a pension scheme (Alecta ITP 1/ITP2), a generous wellness stipend, other insurances, and a substantial amount of professional development opportunities inside and outside the school. We also offer staff events and social gatherings that bring colleagues together, for example, hobby evenings and choir practices. Our location in central Stockholm is easily accessible by public transportation. Contract details: Temporary Cover Contract Time allocation: 100% Starting: August 7, 2026 Ending: December 18, 2026 Salary: Based on salary scale. Application: Last day for application: Tuesday, July 28, 2026. We only accept applications in English and from certified candidates. SIS holds the right to offer the position as soon as a viable candidate is found. Please send your letter of interest and CV to application@intsch.se. Please write [Middle School Science Teacher] in the Subject Line.

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

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