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 2300 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. In this context, we are looking for a
Your tasks
- 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 optimize the structure of accident progression models and their success criteria
Your profile
- Master’s degree in nuclear engineering or other engineering disciplines (e.g. mechanical, chemical) with knowledge of nuclear systems
- Familiarity with several accident computational codes, especially MELCOR
- Familiarity with computational programming (e.g. use of 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
We offer
Our institution is based on an interdisciplinary, innovative and dynamic collaboration. You will profit from a systematic training on the job, in addition to personal development possibilities and our pronounced vocational training culture. If you wish to optimally combine work and family life or other personal interests, we are able to support you with our modern employment conditions and the 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.
For further information, please contact Dr Luca Podofillini, e-mail luca.podofillini@psi.ch, phone +41 56 310 53 56 or Dr Mateusz Malicki, e-mail mateusz.malicki@psi.ch, phone +41 56 310 21 27.
Please submit your application online by 30 June 2026 including addresses of referees) for the position as a PhD Student in Probabilistic Modelling of Severe Nuclear Accident Risk (Index-Nr. 4103-28180).
Paul Scherrer Institute, Human Resources Management, Serdal Varol, 5232 Villigen PSI, Switzerland