Uppsala University
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PhD student 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 Sweden. The project sits in the Division of Applied Nuclear Physics and focuses on reactor physics, nuclear engineering, machine learning, optimisation, and computational methods for core and fuel optimisation.
The research is part of an ongoing PhD project on small modular reactors (SMRs) within the competence centre ANItA (Academic-industrial Nuclear technology Initiative to Achieve a sustainable energy future). The work combines physics-based reactor models with modern optimisation and data analysis methods, including machine-learning-based surrogate models, graph-based representations of core loading patterns, uncertainty quantification, and improved handling of physical constraints.
Typical tasks include developing and applying surrogate models for reactor-physics calculations, evaluating optimisation methods for fuel loading patterns and fuel composition, analysing safety-related parameters such as reactivity, power distributions, fuel utilisation and margins, working with large simulation datasets, and implementing tools in Python or similar languages. The successful candidate will also publish papers, present at conferences, and participate in seminars and project meetings.
This is a doctoral opening with 100% employment and a temporary appointment under the Higher Education Ordinance. The position is based in Uppsala, with a planned start date of 1 January 2027 or as agreed. The application deadline is 30 September 2026.
Eligibility requires a relevant Master’s degree or equivalent credits in engineering physics, nuclear engineering, energy engineering, machine learning, computer science, applied mathematics, or a related field. Applicants should have good knowledge of physics, numerical methods and/or machine learning, strong programming skills, good English, and the ability to work independently and collaboratively. Experience in reactor physics, core optimisation, fuel cycle analysis, neural networks, stochastic or multi-objective optimisation, HPC, and reproducible workflows is considered a merit.
To apply, submit your materials through Uppsala University’s recruitment system and include your transcript, degree project, and supporting documents. The cover letter has been 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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