Ph.D. Position in Computer Science (Wearable Intelligence & Data Fusion)

Constructor Knowledge Labs

ABOUT THE POSITION You are expected to conduct and lead internationally competitive research in AI-driven semantic analysis and automated reasoning-flow modeling, with applications to educational materials, scientific documents, and research authoring. Your work will focus on developing advanced methods for semantic structure extraction, conceptual and argumentative flow reconstruction, rationale-aware content generation, metacognitive prompting, and adaptive personalization. Core research contributions will include designing algorithms for concept and structure extraction, building neural/graph hybrid models for pedagogical reasoning, implementing ontology-alignment methods for cross-domain transfer, and creating human-in-the-loop optimization pipelines that incorporate expert feedback—aligning with the multi-year research roadmap (WP1–WP3) . As a postdoctoral researcher, you will take a leading role in designing experiments, shaping research directions, supervising junior researchers (including PhD students), and contributing to the development of end-to-end demonstrator systems capable of generating structured, rationale-rich, and learner-adaptive content. You will be responsible for coordinating data annotation efforts, overseeing the construction of evaluation frameworks, and driving publication-quality research outputs, including survey papers, methodology papers, and cross-domain transfer studies. Interdisciplinary collaboration is strongly encouraged, especially at the intersection of computer science, computational linguistics, cognitive science, and learning technologies, and you will have opportunities to initiate or co-lead joint projects with internal and external partners. The postdoctoral researcher will also contribute to teaching in areas such as Machine Learning, NLP, AI for Education, Explainable AI, and Python-based applied seminars, supporting course development and supervising Bachelor’s, Master’s, and PhD theses. The university provides a supportive academic environment—including mentoring, administrative support, computational resources, and opportunities for technology transfer and industry engagement—enabling the postdoctoral researcher to establish or strengthen an internationally visible research profile. ---------------------------------------------------------------------------------------------------------------------------------- MANDATORY REQUIREMENTS * PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a closely related field. * Strong publication record in relevant top-tier venues (e.g., NeurIPS, ACL, ICML, ICLR, AIED, LAK, AAAI). * Demonstrated expertise in at least two of the following areas: * semantic parsing or structured NLP * knowledge representation, reasoning graphs, or GNNs * natural language generation, explainability, or rationale modeling * ontology alignment, cross-domain transfer, or representation learning * personalization algorithms, metacognition, or educational AI * human-in-the-loop systems or RLHF * Experience in leading research tasks, mentoring junior researchers, and coordinating multi-stage projects. * Fluency in Python and modern deep learning frameworks (PyTorch/TensorFlow). * Strong analytical, communication, and academic writing skills. * Demonstrable ability to design rigorous experimental pipelines and validation methodologies. * Responsible, independent, and proactive research personality with strong teamwork skills. * Intercultural experience and readiness to work in an international research environment. * Fluency with AI co-pilot assistants for coding and writing. * Fluency in English, the primary language of research and instruction on campus. PREFERRED QUALIFICATIONS: * Experience in developing research prototypes, evaluation benchmarks, or large-scale datasets. * Prior involvement in interdisciplinary or applied research projects. * Potential to contribute to competitive funding applications. * Experience with open-source releases or reproducible research pipelines. APPLICATION DETAILS * Starting date: March, 2026 * Contract: Full-time (100%), TV-L E13 * Work mode: Hybrid APPLICATION PACKAGE MUST INCLUDE:  * Curriculum Vitae (CV); * A detailed letter of motivation outlining research interests and career goals; * 2 recommendation letters; Applications to be reviewed on a rolling basis. Shortlisted candidates will be invited to interviews.

Constructor Knowledge Labs

About the Position Constructor University, in collaboration with Constructor Knowledge Labs (CKL) and Constructor Technology (industry partner), invites applications for a PhD position in the field “Information Systems and Management” within the research group of Professor Isak Frumin https://www.linkedin.com/in/isak-frumin-337780b1/. The position focuses on the transformation of higher education and the science industry in the era of artificial intelligence. It offers an opportunity to engage in high-impact applied research, collaborate with leading experts, and contribute to publications and policy-relevant outputs. The project includes cross-country monitoring (through an expert network and dedicated research) of demand and innovative practices, providing regular updates on emerging developments. The research will examine how universities and research institutions are adapting their educational and research practices in response to AI technologies. Key questions include: * What new best practices of the use AI are emerging, and in which areas of science and higher education do they appear most rapidly? * Which universities, groups, and individuals act as early adopters and innovators in the use of AI tools?   Funding The project is funded by a stipend from Constructor Technology in accordance with German regulations, with the possibility of an additional mini-job, research cost allowance and a health insurance subsidy Constructor University Bremen actively supports candidates in preparing applications for external funding — doctoral scholarships, foundations, or international mobility grants — and can provide institutional support and references Location: Bremen, Germany Start date: fall 2026 Mandatory requirements: * Master’s degree in sociology, economics, political science, higher education studies, public policy, science and technology studies, data science or a related social science discipline. * Strong analytical, research, and writing skills; experience with quantitative and qualitative research and case studies is a plus. * Hands-on research experience, evidenced through publications, thesis work, or open-source contributions. * Excellent academic English writing skills, demonstrated through peer-reviewed papers, reports, or equivalent outputs. Preferred qualifications: * Demonstrated interest in AI applications in higher education and research governance. * Skills and experience in data collection, analysis, visualization * Some proficiency in German (speaking or writing) is desirable but not mandatory * Applications from PhD students currently based in EU are particularly encouraged Application package must include:  * Cover letter (1–2 pages) explaining your motivation, research interests, and fit with the project * CV (including publications or research projects) * Master's degree certificate and transcripts * Contact information for 2–3 possible academic referees * English proficiency certificate (if applicable) * Optional: sample of research writing (e.g., thesis, policy report, or publication) Applications should be submitted https://job-boards.eu.greenhouse.io/constructorknowledgelabs Applications to be reviewed on a rolling basis. Shortlisted candidates will be invited to interviews.

Lyft

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. RESPONSIBILITIES: * Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. * System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. * Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically evaluating new research and identifying high-impact use cases across business areas. * Collaboration: Partner with ML engineers, product managers, data scientists, and software engineers to align ML initiatives with business goals. * Data-Driven Decision Making: Leverage data-driven insights to inform and refine ML strategies and solutions. * Mentorship & Technical Leadership: Provide technical direction, mentor Junior engineers, and foster a culture of learning and collaboration. * Code Quality: Write production-level code and participate in code reviews to ensure quality and share knowledge across the team. EXPERIENCE: * * M.S. or Ph.D. in Computer Science or related technical field * 5+ years (or Ph.D. with 3+ years) of experience in machine learning modelling or related fields * Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks * Understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learning * Experience with translating state-of-the-art ML research into production systems * Proficiency in Python, Golang, or other programming language * Proven ability to tackle ambiguous problems and deliver solutions at scale. * Strong communication and interpersonal skills for effective cross-functional collaboration. BENEFITS: * Great medical, dental, and vision insurance options with additional programs available when enrolled * Mental health benefits * Family building benefits * Child care and pet benefits * 401(k) plan with company match to help save for your future * In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off * 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible * Subsidized commuter benefits * Monthly Lyft credits and complimentary Lyft Pink membership Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law. Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid The expected base pay range for this position in the San Francisco area is $162,800 - $203,500, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.