Postdoctoral Researcher in Probabilistic Methods for Foundation and World Models

Uppsala Universitet · Full-time

box 256, Uppsala, Sweden

Would you like to work with probabilistic machine learning for the next generation of AI models in an international environment with competent and pleasant colleagues? We welcome your application for a postdoctoral position at Uppsala University. This is an abbreviated version of the job posting. The complete posting is available on Uppsala University's website, uu.se/jobb. The Department of Information Technology is Uppsala University's third-largest department with over 350 employees and participates in the Wallenberg AI, Autonomous Systems and Software Program (WASP). More information is available on the department's website. The position is located at the Division of Scientific Computing (TDB), one of the world's largest research environments in scientific computing and an important part of the e-science collaboration eSSENCE and Science for Life Laboratory (SciLifeLab), a national research infrastructure for life sciences. You will join the Scientific Machine Learning research group at TDB and SciLifeLab. The group develops theory, methods, and software for data-driven science, with a focus on uncertainty quantification in large pre-trained models, generative models, simulation-based inference, and robust and active learning. Project Description The position offers significant scientific freedom within the theme of probabilistic methods for foundation models and world models: making them uncertainty-aware, calibrated, robust, and useful for scientific decision-making. You may build on one of the following areas or propose your own topic within the theme (describe your research direction, max 2 pages): Uncertainty quantification, calibration, and reliability in large pre-trained models. Probabilistic generative models and world models. Probabilistic machine learning for scientific discovery. Motivating applications exist in the life sciences, where the group collaborates through SciLifeLab in areas such as microscopy, drug development, and precision medicine, with access to real, large-scale, and multimodal data. The emphasis is on high-quality fundamental AI/ML methodological contributions that applications can benefit from. Duties Research, publishing and conference presentations, contributions to the group's open-source software, and participation in student supervision. A limited amount of teaching may be included (maximum 20%). Qualifications A doctoral degree in machine learning, computer science, computational science, mathematics, statistics, or a closely related field, or a foreign degree assessed as equivalent to a doctoral degree in one of these areas. The degree must be completed by the time the employment decision is made. Preferably, the degree should have been obtained no more than three years ago. When calculating the three-year period, the starting point is the final application deadline. If there are special reasons, such a degree may have been obtained earlier. Special reasons include leave due to illness, parental leave, positions of trust within trade union organizations, etc. Documented research experience with modern deep learning and very good programming skills in Python and a modern deep learning framework (e.g., PyTorch or JAX) are required. Good knowledge of English in speech and writing is required. Candidates must clearly demonstrate a high degree of self-motivation in their application. Great weight is placed on personal qualities such as creativity, accuracy, a structured approach, and the ability to work both independently and in a team. Desirable/Meritorious Experience Publications at leading machine learning or computer vision conferences (NeurIPS, ICML, ICLR, CVPR, etc.) are strongly meritorious. Expertise in Bayesian methods, generative models, multimodal models, world models, or simulation-based inference is meritorious, as is experience with large-scale training on GPU clusters, open-source software development, and applications in the life sciences. Teaching experience is meritorious but not required. Teaching experience may include, for example, instruction, supervision, mentoring, work as a teaching assistant, internal training, or other educational activities, within or outside higher education. Particular weight is placed on activities that support students' learning in computer science, information technology, or related subjects. Application Your application must include: A curriculum vitae (CV), A copy of relevant grade documents (translated into Swedish or English), A list of publications, Up to five selected publications in electronic format, A research description describing your previous and current research (max 1 page) and a proposal for future activities (max 1 page), Contact information for two references, About the Position The position is time-limited for two years according to central collective agreement. The position is full-time. Start date: November 1, 2026 or by agreement. Work location: Uppsala Information about the position is provided by: University Lecturer Prashant Singh, [email protected]; Division Head Elisabeth Larsson, [email protected]. In this recruitment, we have replaced the cover letter with questions that you answer as part of your application. The answers will be used as part of the selection process. Welcome to submit your application by Thursday, October 15, 2026, UFV-PA 2026/2764 Uppsala University is a broad research university with a strong international position. The ultimate goal is to conduct education and research of the highest quality and relevance to make a difference in society. Our most important asset is all 7,500 employees and 53,000 students who with curiosity and commitment make Uppsala University one of the country's most exciting workplaces. Read more about our benefits and what it's like to work at Uppsala University https://uu.se/om-uu/jobba-hos-oss/ The position may be subject to security clearance. For security clearance to be conducted, it is a requirement for employment that the applicant is approved. We decline offers of recruitment and advertising assistance. Applications are received through Uppsala University's recruitment system. Trade union representatives: Saco-S - [email protected], Seko - [email protected], ST (OFR/S) - [email protected]