Overview
Uppsala University is recruiting one full-time PhD student to develop statistical and machine-learning methods for nuclear fuel performance modelling, uncertainty quantification and fast simulation. The project is carried out with industrial collaboration involving Westinghouse and Vattenfall.
Complete research opportunity details
The doctoral project sits in the Department of Physics and Astronomy and includes model calibration, uncertainty propagation, temporal machine-learning surrogate models, scientific computing and industrially relevant nuclear-fuel applications. Employment is a 100% temporary doctoral position with a fixed salary, planned to start 1 January 2027 or as agreed. Teaching or other departmental duties may comprise up to 20% of full-time employment.
Eligibility requirements
Applicants must meet doctoral-study entry requirements, such as a relevant Master's degree or equivalent higher-education background. Relevant fields include engineering physics, nuclear engineering, applied physics, energy engineering, computational science, applied mathematics, statistics and machine learning. The position also requires relevant physics/numerical/statistical or ML knowledge, programming skills such as Python, Julia or C++, collaboration skills and good spoken and written English.
Tips for this phd opportunity
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- Match your research background to the project, laboratory, supervisor and required methods rather than applying only from the title.
- Prepare a focused academic CV, transcripts, publications and research statement or proposal when requested by the official call.
- Confirm funding duration, stipend/salary, tuition coverage, start date and eligibility for international applicants.
- Contact a supervisor before applying only when the official instructions recommend or require it.
Verification notes
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