Funded Studentships

You can use our search listing to find the right project for your skills, passion and expertise. The listing includes:

  • An extensive portfolio of PhD projects, with expert supervisory teams based in one of our leading research centres.
  • A number of PhD programmes with international partner universities around the world.

Please note: projects are updated regularly.

You may also be interested in our PhD by Publication.

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Fast multi-wavelength variability of accreting compact objects

Black holes and neutron stars in binary systems pull matter from a companion star, forming a hot, accretion disc and often launching powerful jets of material at close to the speed of light. These systems flicker rapidly, with their brightness changing on timescales of less than a second. This variability carries information about regions far too small to image directly. This project will use observations taken at the same time in X-rays, optical and infrared light, with some of the world's leading space- and ground-based telescopes, to track how these flickers travel through the system. Using time-series analysis and modelling, the student will measure how fast the jets move, how close the disc reaches to the central object, and how strong the magnetic fields are.

Gen AI and Student Feedback Literacy Coventry led Studentship

This project examines how university students’ feedback literacy is transforming amid widespread GenAI adoption, which is a critical challenge for educators and policymakers globally. Focusing on learner agency, the successful candidate will explore whether feedback opportunities effectively engage students, despite persistent disengagement. Project outcomes will inform curricular design, institutional support strategies, and pedagogical practices, to bridge gaps between theory and real-world engagement. Candidates from a range of disciplinary backgrounds are welcome to apply. Experience of social science research approaches is needed.

AI-Enhanced EMC Digital Twin for Automotive WBG Converters

This PhD studentship develops an AI-driven Digital Twin framework for Electromagnetic Compatibility (EMC) in Wide-Bandgap (SiC/GaN) power converters used in automotive applications. The project will develop predictive surrogate models using Physics-Informed Neural Networks (PINNs) and Gaussian Process Regression (GPR) to predict high-frequency conducted and radiated emissions, bridging virtual simulations with real-world physical compliance testing.

Gen AI and Student Feedback Literacy Deakin Led Studentship

This project examines how university students’ feedback literacy is transforming amid widespread GenAI adoption, which is a critical challenge for educators and policymakers globally. Focusing on learner agency, the successful candidate will explore whether feedback opportunities effectively engage students, despite persistent disengagement. Project outcomes will inform curricular design, institutional support strategies, and pedagogical practices, to bridge gaps between theory and real-world engagement. Candidates from a range of disciplinary backgrounds are welcome to apply. Experience of social science research approaches is needed.