Postdoc in probabilistic methods for foundation and world models

Do you want to work with probabilistic machine learning for next-generation AI models in an international environment with competent and pleasant colleagues? Welcome to apply for a postdoctoral position at Uppsala University.

This is a shortened version of the advertisement. The full advertisement can be found 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 can be found on the department's website.

The position is located at the Department of Computational Science (TDB), one of the world's largest research environments in computational science and an important part of the e-science collaboration eSSENCE and of the Science for Life Laboratory (SciLifeLab), a national research infrastructure for the life sciences.

You will be part of the Scientific Machine Learning research group at TDB and SciLifeLab. The group develops theory, methods, and software for data-driven science, focusing on uncertainty quantification in large pretrained models, generative models, simulation-based inference, as well as robust and active learning.

Project description The position offers great 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 can start from one of the following or propose your own topic within the theme (describe your research focus, max 2 pages): Uncertainty quantification, calibration, and reliability in large pretrained models. Probabilistic generative models and world models. Probabilistic machine learning for scientific discovery.

Motivating applications exist within the life sciences, where the group, via SciLifeLab, collaborates 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 method contributions that applications can benefit from.

Tasks Research, publication, and conference presentations, contribution to the group's open software, as well as participation in the supervision of students. A limited portion of teaching may be included (at most 20%).

Qualification requirements A doctoral degree in machine learning, computer science, computational science, mathematics, statistics, or a related field, or a foreign degree assessed to correspond to a doctoral degree in one of these fields. The degree must be completed no later than when the employment decision is made. Primarily, candidates who have obtained their degree at most three years ago should be considered. When calculating the three-year period, the starting point is the application deadline. If there are special reasons, such a degree may have been obtained earlier. Special reasons refer to leave due to illness, parental leave, positions of trust within trade unions, etc.

Documented research experience in modern deep learning as well as very good programming skills in Python and a modern deep learning framework (e.g., PyTorch or JAX) are required. Good proficiency in English, both spoken and written, is required. The candidate must clearly document a high degree of self-motivation in the application. Great importance is placed on personal qualities such as creativity, precision, a structured way of working, and the ability to work both independently and in a team.

Other desirable/merit-based qualifications Publications at leading machine learning or computer vision conferences (NeurIPS, ICML, ICLR, CVPR etc.) are highly 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 software development, and applications within the life sciences.

Teaching experience is meritorious but not a requirement. Teaching experience may include, for example, teaching, supervision, mentorship, work as a teaching assistant, internal training, or other pedagogical activities, within or outside higher education. Particular weight is placed on activities that support student learning in computer science, information technology, or related subjects.

Application The application must include:

• A curriculum vitae (CV),
• A copy of relevant transcripts (translated into Swedish or English),
• A publication list,
• Up to five selected publications in electronic format,
• A research description describing your past and current research (max 1 page) and a proposal for future activities (max 1 page),
• Contact information for two references,

About the employment

The employment is fixed-term for two years according to the central collective agreement. The scope is full-time. Commencement: November 1, 2026, or as agreed. Location: Uppsala

Information about the employment is provided by: Associate Professor Prashant Singh, prashant.singh@scilifelab.uu.se; Head of Department Elisabeth Larsson, elisabeth.larsson@it.uu.se.

In this recruitment, we have replaced the personal letter with questions that you answer in connection with your application. The answers will be used as part of the selection process.

Welcome with your application no later than 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 engagement, make Uppsala University one of the country's most exciting workplaces.

Read more about our benefits and what it is like to work at Uppsala University

https://uu.se/om-uu/jobba-hos-oss/

The employment may be subject to security clearance. In the case of security clearance, approval of the applicant is a prerequisite for employment.

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Applications are received in Uppsala University's recruitment system.

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