PhD Studentship – Intelligent Modelling of Self-Organised Edge Turbulence in Tokamak Plasmas
Coventry University – Centre for Fluid and Complex Systems (CFCS)
Coventry, United Kingdom
Coventry University is offering a fully funded PhD studentship within the Centre for Fluid and Complex Systems (CFCS), focusing on the intelligent modelling of self-organised edge turbulence in tokamak plasmas. This project sits at the forefront of fusion energy research and aims to advance understanding of plasma turbulence, a critical challenge in the development of sustainable nuclear fusion technologies.
The research will investigate the complex, nonlinear dynamics of edge turbulence in magnetically confined plasmas, particularly within tokamak devices. The successful candidate will apply advanced computational modelling techniques, including machine learning and data-driven approaches, to develop predictive and interpretable models of turbulence behaviour. The project is expected to contribute to improved plasma confinement strategies and inform the design and operation of future fusion reactors.
The candidate will work within a multidisciplinary research environment, collaborating with experts in fluid dynamics, plasma physics, applied mathematics, and computational science. The role includes conducting theoretical and numerical research, analysing large datasets, developing simulation tools, and disseminating findings through high-quality publications and conference presentations. Access to high-performance computing resources and advanced training opportunities will be provided.
Eligibility Criteria
Applicants should hold, or expect to obtain, a first-class or upper second-class honours degree (or equivalent) in physics, applied mathematics, engineering, or a closely related discipline. A master’s degree in a relevant subject is desirable but not essential. Candidates must meet Coventry University’s postgraduate research admission requirements, including English language proficiency where applicable.
Required expertise/skills
A strong background in mathematics, physics, or computational science is essential. Experience with numerical modelling, programming (such as Python, MATLAB, or C/C++), and data analysis is highly desirable. Familiarity with plasma physics, fluid dynamics, nonlinear systems, or machine learning techniques would be advantageous. Candidates should demonstrate strong analytical and problem-solving skills, along with the ability to work independently and collaboratively in a research environment. Effective written and verbal communication skills are required.
Salary details
The studentship includes full tuition fee coverage and a tax-free stipend in line with UKRI rates. Additional support for research training, travel, and conference participation may be available.
Application Deadline
Not specified