Eun-jin Kim

[Fully funded PhD studentship including tuition fees and stipend.] This fully funded PhD studentship at Coventry University Group offers an exciting opportunity to advance the understanding and predictive modelling of turbulence and instability dynamics at the edge of tokamak plasmas. The project is part of the UK Fusion Centre for Doctoral Training (Fusion CDT), focusing on the challenge of turbulent transport in high-temperature fusion plasmas—a key barrier to achieving reliable, high-performance fusion energy. The research aims to develop intelligent models that blend physics-based approaches with modern AI and machine learning techniques, enabling real-time analysis and control of complex plasma behaviour. As a PhD student, you will study plasma physics and turbulence, develop and apply computational models, and join a national training cohort collaborating with partners such as NTU, the KSTAR team, and Deakin University. The project welcomes applicants from physics, mathematics, engineering, and related fields, and provides comprehensive research training, including technical, personal, and professional skills. All researchers at Coventry University benefit from the Doctoral and Researcher College, which supports high-quality training and career development. Entry requirements include a minimum of a 2:1 first degree in a relevant discipline, with at least 60% in the project element or equivalent and a minimum 60% overall module average. Candidates must demonstrate the potential to engage in innovative research and complete the PhD within 4 years. English language proficiency is required, with an IELTS academic overall minimum score of 6.5 and at least 6.0 in each component. The studentship covers full tuition fees and provides a stipend. Applications should be submitted via the Coventry University PGR Plus portal. Applicants must provide full supporting documentation, a covering letter, and a 500-word supporting statement outlining their expertise and interest in the project. For further information, contact Professor Eun-jin Kim. The application deadline is 25 April 2026.