PhD Student in Probabilistic Modelling of Severe Nuclear …, Villigen

PhD Student in Probabilistic Modelling of Severe Nuclear Accident Risk The Paul Scherrer Institute PSI is the largest research institute for natural and engineering sciences within Switzerland. We perform cutting‑edge research in the fields of future technologies, energy and climate, health innovation and fundamentals of nature. By performing fundamental and applied research, we work on sustainable solutions for major challenges facing society, science and economy. PSI is committed to the training of future generations. Therefore, about one quarter of our staff are post‑docs, post‑graduates or apprentices. Altogether, PSI employs 2,300 people.

In this doctoral research project, the Risk and Human Reliability (RHR) group in the Laboratory for Energy Systems Analysis and the Severe Accident Research (SACRE) group in the Laboratory for Reactor Physics and Thermal‑Hydraulics are developing graphical, probabilistic models (Bayesian Networks) to represent and analyse severe accident uncertainties in nuclear power plants. In particular, we are exploring their use as surrogates for accident simulation codes in the frame of the Probabilistic Safety Assessment (PSA) of severe accident risks.

Responsibilities

Design and implement the uncertainty analysis study for severe accidents in nuclear power plants (includes running sets of accident simulation codes such as MELCOR, MAAP)

Develop and evaluate different Bayesian Network models (from different structural learning and quantification algorithms) for surrogate modelling

Demonstrate the application of these models for two major use cases for nuclear Probabilistic Safety Assessment (PSA): examining the impact of uncertainties on the PSA outcomes of interest for model validation and integrating uncertainty analysis findings in PSA models to optimise the structure of accident progression models and their success criteria

Qualifications

Master’s degree in nuclear engineering or other engineering disciplines (e.g., mechanical, chemical) with knowledge of nuclear systems

Familiarity with accident computational codes, especially MELCOR

Familiarity with computational programming (e.g., Python, R, Matlab)

Familiarity with machine learning techniques or causal discovery algorithms is ideal, but not a requirement

Very good knowledge of English is required, written and oral

Benefits Our institution is based on an interdisciplinary, innovative and dynamic collaboration. You will profit from systematic training on the job, in addition to personal development possibilities and a pronounced vocational training culture. If you wish to optimally combine work and family life or other personal interests, we support you with modern employment conditions and on‑site infrastructure. The work will be carried out at the Paul Scherrer Institute, in Villigen, Switzerland. The PhD degree will be awarded by the Swiss Federal Institute of Technology Zurich (ETHZ).

Contact For further information, please contact Dr. Luca Podofillini, e‑mail , phone +41 56 310 53 56 or Dr. Mateusz Malicki, e‑mail , phone +41 56 310 21 27.

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