Your Tasks
- Design and implement the uncertainty analysis study for severe accidents in nuclear power plants, including the execution of accident simulation codes such as MELCOR and MAAP.
- Develop and evaluate various Bayesian Network models using different structural learning and quantification algorithms for surrogate modeling.
- Demonstrate the application of these models for two major use cases in nuclear Probabilistic Safety Assessment (PSA):
- Examine the impact of uncertainties on PSA outcomes for model validation.
- Integrate uncertainty analysis findings into PSA models to optimize the structure of accident progression models and their success criteria.
Your Profile
- Master's degree in nuclear engineering or related engineering disciplines (e.g., mechanical or chemical) with a solid understanding of nuclear systems.
- Familiarity with several accident computational codes, particularly MELCOR.
- Experience in computational programming (e.g., Python, R, Matlab).
- Familiarity with machine learning techniques or causal discovery algorithms is a plus but not a requirement.
- Proficient in English, both written and spoken.
We Offer
Our institution fosters interdisciplinary, innovative, and dynamic collaboration. You will benefit from systematic on-the-job training, personal development opportunities, and a strong vocational training culture. We support a healthy work-life balance with modern employment conditions and excellent on-site infrastructure, ensuring you can pursue both professional and personal interests effectively.
The work will take place at the Paul Scherrer Institute in Villigen, Switzerland. The PhD degree will be awarded by the Swiss Federal Institute of Technology Zurich (ETHZ).
Contact Information
For further inquiries, please reach out to:
Apply online using the form below. Only applications matching the job profile will be considered.
Paul Scherrer Institute, Human Resources Management, Serdal Varol, 5232 Villigen PSI, Switzerland