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PhD in Core Optimisation Using Machine Learning at Uppsala University Uppsala University in Sweden
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
Sep 30, 2026
Country
Sweden
University
Uppsala University
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About this position
Uppsala University is advertising a PhD student position in core optimisation using machine learning at the Department of Physics and Astronomy in Uppsala, Sweden.
The project sits in applied nuclear physics and focuses on reactor physics, nuclear engineering, core optimisation, fuel cycle analysis, fuel management, and machine learning. The research is part of the ANItA competence centre and continues work on optimisation for small modular reactors (SMRs), combining physics-based simulation with modern optimisation and data-driven surrogate models.
Possible research directions include cycle-to-cycle optimisation, new machine learning models, improved optimisation strategies, uncertainty quantification, handling physical constraints more efficiently, and analysis of fuel design, loading patterns, and safety-related quantities. The role involves developing, implementing, and evaluating computational methods, working with large simulation datasets, and coding tools such as Python.
Eligibility: a relevant Master’s degree or equivalent higher-education background is required. The post also asks for good knowledge of physics, numerical methods and/or machine learning, strong programming skills, independent and structured working style, collaboration skills, and excellent English. Experience with reactor physics, neural networks, graph neural networks, surrogate modelling, optimisation algorithms, HPC, and reproducible workflows is considered a merit.
Funding and employment: this is a temporary doctoral employment at 100% with fixed salary. Teaching and other departmental duties may be included up to 20% of full-time work.
Deadline: 30 September 2026. Location: Uppsala, Sweden.
How to apply: submit the application via Uppsala University’s recruitment system and attach your transcript of records, degree project, and any supporting documents. The cover letter is replaced by application questions in the portal.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
More information can be found here
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