Doctoral student in Explainable Machine Learning for Nuclear Safeguards
Explore AI-driven nuclear safeguards by developing transparent artificial neural networks for spent nuclear fuel inspection.
Best for:Best for candidates with a Master's degree in physics, mathematics, or computer science and a strong background in machine learning and Python programming.
Overview
Chalmers University of Technology invites applications for a fully funded doctoral student position in the Reactor Physics, Modelling and Safety group. The research focuses on designing an Explainable Artificial Intelligence framework to make complex artificial neural networks transparent for spent nuclear fuel safeguards inspection. The successful candidate will investigate semantic layers, optimize model architectures, and publish scientific findings in peer-reviewed journals. In addition to research, the role involves advanced coursework within the Graduate School of Nuclear Engineering and up to twenty percent departmental teaching or related duties.
What you'll do
- Conduct doctoral research focused on developing, testing, and evaluating an Explainable AI framework for spent nuclear fuel safeguards inspection.
- Integrate various explainable artificial intelligence methods and investigate semantic layers to translate model predictions into actionable explanations.
- Leverage insights from explainable AI to guide artificial neural network architectures, optimize training strategies, and improve model robustness.
- Formulate independent scientific concepts and disseminate research outcomes through peer-reviewed journal articles and conference presentations.
- Complete advanced coursework within the Graduate School of Nuclear Engineering.
- Participate in undergraduate teaching or other departmental duties corresponding to twenty percent of working hours.
Requirements
Degree required: Master's degree (120 credits) or magisterexamen (60 credits) in Physics, Mathematics, Computer Science, or equivalent (or a 4-year Bachelor's degree for students educated outside Sweden)
Degree offered: PhD
Language: English; strong written and verbal communication skills
Instruction: English
- Background or experience in Machine Learning, Deep Learning, Explainable AI, Reactor Physics, or Nuclear Safeguards
- Solid foundation in computational methods and strong programming skills in Python
- Strong analytical mindset with the ability to solve complex technical challenges
- Ability to work collaboratively and take personal responsibility for research progress
- Must meet general entry requirements for doctoral studies at Chalmers University of Technology
- Must be able to maintain physical presence in Gothenburg throughout the study period
- Must present a valid residence permit by the study start date if applicable
Funding & terms
How to apply
Deadline: 2026-11-23
Prepare all required application documents in English as PDF files under the specified size limit. Submit the complete application package through the official online portal by the stated deadline. Incomplete applications or those submitted via email will not be considered.
- CV
- Personal letter
- Bachelor's thesis and transcripts
- Master's thesis and transcripts
Contact
Paolo Vinai· Associate Professor
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