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
Temporary full-time PhD employment according to the Higher Education Ordinance. Scope of employment is 100%. The post is a salaried doctoral position; no stipend amount or tuition details are stated.
Deadline
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
Temporary full-time PhD employment according to the Higher Education Ordinance. Scope of employment is 100%. The post is a salaried doctoral position; no stipend amount or tuition details are stated.
What's required
Applicants must meet doctoral entry requirements by holding a Master’s degree in engineering physics, nuclear engineering, energy engineering, machine learning, computer science, applied mathematics or another relevant area, or by having completed at least 240 higher-education credits including at least 60 credits at Master’s level and an independent project worth at least 15 credits, or equivalent knowledge. Required qualifications include good knowledge of physics, numerical methods and/or machine learning, good programming skills (for example Python, Julia or C++), ability to work independently and in a structured manner, collaboration skills, and strong spoken and written English. Personal qualities such as analytical ability, initiative, accuracy and motivation are emphasized. Experience in reactor physics, nuclear engineering, neutron transport, core optimisation, fuel cycle analysis, machine learning, graph neural networks, surrogate modelling, optimisation algorithms, uncertainty quantification, scientific computing, HPC, version control, and reproducible workflows is a merit.
How to apply
Prepare and submit the application through Uppsala University's recruitment system. Attach your transcript of records, a copy of your degree project, and any other supporting documents you want to rely on. The application replaces the cover letter with questions to answer in the portal.
More information can be found here
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