PhD Studentship in Mechanical Engineering and AI for Fusion Breeder Blankets

This PhD position focuses on the critical challenge of tritium breeding in future fusion power plants. The research will explore the optimization of the Tritium Breeding Ratio (TBR) through advanced modeling techniques, including Monte Carlo methods and machine learning. The candidate will collaborate with a team of researchers and doctoral students, contributing to the development of predictive methodologies for fusion reactor designs. Applicants should be prepared to engage with complex thermomechanical challenges and utilize AI approaches for data analysis.

• Investigate the optimization of Tritium Breeding Ratio (TBR) in fusion reactors.
• Employ Monte Carlo methods to model neutron transport and tritium breeding.
• Develop predictive methodologies using machine learning techniques.
• Collaborate with researchers and doctoral students in related fields.
• Analyze data from international fusion datasets and literature.