Postdoctoral Researcher in Nuclear Data Uncertainty Quantification, Reactor Noise, and Spent Fuel Analysis

The research conducted at the Department of Physics and Astronomy encompasses a wide range of physics topics, distributed over nine divisions. The department is located in the Ångström laboratory and employs nearly 400 people, 100 of whom are doctoral students. It offers a broad physics curriculum to undergraduate and graduate students, participation in nationally and internationally leading projects for researchers, and opportunities for partnership with industry and various outreach activities. Read more on www.uu.se/physics

Uppsala University is seeking a highly motivated Postdoctoral Researcher to join our research team in applied nuclear physics. The position is connected to the research programme MÅSTE, Multidisciplinary Commitments for Sweden’s Gen IV Technology and Expertise, which addresses key scientific and technical challenges for future Generation IV reactor systems. More information about the programme is available at: https://www.maste.nu/

The postdoctoral project will focus on nuclear data uncertainty quantification for Generation IV reactor systems, with particular emphasis on neutron-noise-based core monitoring and spent nuclear fuel source terms for reprocessing and fuel fabrication.

We are seeking a candidate with a strong background in nuclear engineering, reactor physics, nuclear physics, computational physics, applied mathematics, data science, or a related field. Experience with uncertainty quantification, reactor physics simulations, neutron noise, nuclear data, machine learning, or surrogate modelling is highly relevant. 

The position offers an opportunity to contribute to the development of advanced methods for uncertainty propagation in future reactor systems, with applications ranging from reactor monitoring to the safe handling of the spent nuclear fuel.

Duties

As a Postdoctoral Researcher, you will contribute to the development and application of methods for nuclear data uncertainty quantification in Generation IV reactor systems. The work will include uncertainty propagation from nuclear data to reactor physics observables, with an emphasis on neutron-noise-based core monitoring and the source terms of spent nuclear fuel.

Your key responsibilities will be:

• Research nuclear data uncertainty quantification for Generation IV reactor applications.
• Generate and use random nuclear data files based on nuclear data uncertainties from evaluated libraries
• Process nuclear data into forms suitable for reactor physics and neutron noise calculations, including grouped cross sections when relevant.
• Develop and apply methods for uncertainty propagation to neutron noise-based core monitoring techniques.
• Develop, train, and validate surrogate models for neutron noise prediction codes using machine learning.
• Quantify uncertainties in spent nuclear fuel source terms, including decay heat and inventories of selected nuclides relevant for reactivity, safeguards, safety analysis, reprocessing of spent fuel, and fuel fabrication.
• Lead and contribute to academic publications, conference presentations, and dissemination of research results.
• Collaborate with national and international partners within the research programme.

Requirements

A PhD in nuclear engineering, reactor physics, nuclear physics, computational physics, applied mathematics, data science, or a closely related field, or a foreign degree equivalent to a PhD within one of these fields. The degree must be obtained by the time of the employment decision.

Those who have obtained a PhD degree no more than three years before the application deadline are primarily considered for employment. The starting point of the three-year frame period is the application deadline. Due to special circumstances, the degree may have been obtained earlier. The three years can be extended due to circumstances such as sick leave, parental leave, duties in labour unions, and similar circumstances.

For this position, we also require that the applicant:

• is proficient in at least one programming language.
• has documented experience relevant to reactor physics simulations, nuclear data, uncertainty quantification, or machine learning.
• has good communication skills in both spoken and written English. 

Additional qualifications

Additional qualifications are intended to identify relevant experience and expertise and are considered meriting. We encourage applications even if the applicant does not match all listed qualifications.

• Demonstrated expertise in uncertainty quantification, statistics, applied mathematics, machine learning, or surrogate modelling.
• Experience with reactor physics calculations, nuclear data processing, or nuclear data libraries.
• Experience with neutron noise, reactor noise, time-dependent reactor physics, perturbation methods, or core monitoring techniques.
• Experience with spent nuclear fuel calculations, depletion calculations, decay heat, nuclide inventory calculations, or source term analysis.
• Experience with fast reactor systems, Generation IV reactor concepts, or advanced reactor modelling.
• Strong analytical and problem-solving skills.
• Good communication skills and a strong collaborative spirit.
• Significant research experience in a relevant field.

The application
The application, written in Swedish or English, shall include:

• A personal letter,
• curriculum vitae,
• a copy of the PhD degree certificate and grades from earlier studies,
• a link to (preferably), or a copy of, the PhD thesis
• two references, of which at least one from the academy, and a letter of recommendation,
• publication list, and
• any other documentation that you wish to have considered.

About the employment
The employment is a temporary position of two years according to a central collective agreement. It is a full-time position. Starting date November 2026 or as agreed. Placement: Uppsala.

For further information about the position, please contact: Henrik Sjöstrand henrik.sjostrand@physics.uu.se

Please submit your application by 14 August 2026, UFV-PA 2026/1887.

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