Application
Official vacancy directs applicants to the provider recruitment system; the separate application URL was opened successfully.Uppsala University
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Doctoral researcher
PhD student in core optimisation using machine learning
Uppsala University
Doctoral research extending machine-learning and optimisation methods for small modular reactor core and fuel design within the ANItA competence centre.
The current cycle is confirmed, the official application route is active and a closing date is recorded.
Source review was due 13/08/2026. Confirm details on the official page.
Employment
Vacancy terms
- Career stage
- Doctoral researcher
- Employment type
- PhD candidate employment
- Contract
- Temporary position
- Contract ends
- Not stated
- Original contract term
- Temporary doctoral employment; exact total duration not stated on the vacancy page.
- Schedule
- 1.0 FTE
- Workplace
- Not stated
- FTE
- 1
- Salary
- Fixed salary; amount not stated on the official vacancy page.
- Department or school
- Division of Applied Nuclear Physics, Department of Physics and Astronomy
- Posted
- 17 Jun 2026
Role
Responsibilities
- Develop ML surrogate models for reactor-physics calculations.
- Develop and evaluate fuel-loading and composition optimisation methods.
- Analyse safety parameters and large simulation datasets.
- Implement computational tools.
- Publish scientific articles and present at conferences.
- Teaching may be up to 20%.
Candidate profile
Qualifications and requirements
Qualifications
- Master's degree in engineering physics, nuclear engineering, energy engineering, machine learning, computer science, applied mathematics, or another relevant field; or equivalent doctoral-entry credits/knowledge.
Requirements
- Good knowledge of physics, numerical methods and/or machine learning.
- Good programming skills.
- Ability to work independently and collaboratively.
- Good spoken and written English is required.
Preferred qualifications
- Reactor physics or neutron transport
- Core optimisation or fuel-cycle analysis
- Neural networks, graph neural networks or surrogate modelling
- Optimisation algorithms
- Uncertainty quantification
- HPC and reproducible workflows
Employment conditions
- Temporary position
- Employment scope: 1.0 FTE
- Starting date: 2027-01-01
- Placement: Uppsala
- Fixed salary; amount not stated on the official vacancy page.
Employment package
Benefits
- Fixed salary; amount not stated on the official vacancy page.
- Temporary doctoral employment; exact total duration not stated on the vacancy page.
Application
Documents and steps
Documents
- Transcript of records
- Other supporting documents the applicant wishes to rely on
- Copy of degree project
Steps
Review the official vacancy page and confirm eligibility.
Open the separate official application page.
Sign in or create an account when required.
Complete the application form and upload the provider-stated documents.
Submit before the official closing date.
Official evidence
Why this vacancy is published
This vacancy was checked against the university's official careers system.
Deadline Date
Official vacancy gives a closing date of 2026-09-30.Uppsala University
Eligibility Academic Requirements
Official vacancy states doctoral-entry qualifications including Master's degree in engineering physics, nuclear engineering, energy engineering, machine learning, computer science, applied mathematics, or another relevant field; or equivalent doctoral-entry credits/knowledge..Uppsala University
Funding
Official vacancy states phd candidate employment, 1.0 to 1.0 FTE, with Fixed salary; amount not stated on the official vacancy page..Uppsala University
Research Career Location
Official vacancy places the position in Uppsala, Sweden.Uppsala University
Stable Record Key
Official vacancy identifies PhD student in core optimisation using machine learning with vacancy reference UFV-PA 2026/2129.Uppsala University
Verification Freshness
Closing date 2026-09-30 is after the run date 2026-08-10.Uppsala University
Change history
Published revision history
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Programme continuity
PhD student in core optimisation using machine learning
Use the enduring programme page to check for a verified newer cycle. A closed vacancy never implies that another round is open.
Programme overview and cycle history