Uppsala University
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Postdoc in Probabilistic Methods for Foundation Models and World Models Uppsala University in Sweden
Degree Level
Postdoc
Field of study
Computer Science
Funding
Temporary full-time postdoctoral employment for two years under a central collective agreement. No stipend amount is stated. The position is a salaried employment at Uppsala University.
Deadline
Oct 15, 2026
Country
Sweden
University
Uppsala University
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About this position
Uppsala University is advertising a postdoctoral position in probabilistic methods for foundation models and world models at the Department of Information Technology, hosted by the Division of Scientific Computing and linked to SciLifeLab in Sweden.
The project sits at the intersection of probabilistic machine learning, uncertainty quantification, generative models, Bayesian deep learning, and scientific machine learning. The successful candidate will work on making large pre-trained models and world models more uncertainty-aware, calibrated, robust, and useful for scientific decision-making. Suggested directions include uncertainty quantification and reliability of large models, probabilistic generative models and world models, and probabilistic machine learning for scientific discovery.
The group emphasizes research freedom and encourages bespoke proposals within the theme. The environment includes the Scientific Machine Learning group, collaboration across Uppsala University and SciLifeLab, and access to strong compute resources through national GPU systems and local infrastructure.
Applicants should have a PhD in machine learning, computer science, scientific computing, mathematics, statistics, or a related field, plus documented research experience in modern deep learning, strong Python skills, and excellent English. Experience with PyTorch or JAX, Bayesian methods, multimodal models, simulation-based inference, large-scale GPU training, and open-source software is advantageous. Teaching and supervision experience may also strengthen the application.
The position is full time, temporary for two years, with placement in Uppsala. The application deadline is 2026-10-15. Required application materials include a CV, degree documents, publication list, selected publications, a research statement, and two references. Apply through Uppsala University’s recruitment system via the SciLifeLab career page.
Funding details
Temporary full-time postdoctoral employment for two years under a central collective agreement. No stipend amount is stated. The position is a salaried employment at Uppsala University.
What's required
Applicants must hold a PhD degree in machine learning, computer science, scientific computing, mathematics, statistics, or a closely related field, or an equivalent foreign degree, by the time of the employment decision. Priority is given to candidates who completed the degree within the last three years, with possible extensions for special circumstances. Required experience includes documented research in modern deep learning (e.g. generative models, Bayesian deep learning, or large pre-trained models), excellent Python programming skills with a modern deep learning framework such as PyTorch or JAX, excellent spoken and written English, and clear evidence of self-motivation. Strong creativity, thoroughness, structured problem-solving, and ability to work independently and in a team are important. Teaching experience is a merit, and additional experience with Bayesian methods, generative models, multimodal models, world models, simulation-based inference, large-scale GPU training, open-source software, or life sciences applications is advantageous.
How to apply
Prepare a CV, relevant grade documents translated into Swedish or English, a publication list, up to five selected publications, a research statement with past/current research and future plans, and contact details for two references. Submit the application through Uppsala University’s recruitment system via the provided SciLifeLab career page before the deadline.
More information can be found here
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