TUO
Computational and ML Modelling of Low Temperature Plasmas PhD (CoFunded with Industry)
✓ Fully Funded
⏰ Closing Soon
🎓 Mechanical Engineering
🎓 Theoretical Physics
machine learning
advanced manufacturing
optimisation
numerical simulation
atomic layer deposition
computational physics
data-driven modelling
low-temperature plasma
plasma modelling
This PhD develops computational and machine-learning models to optimise low-temperature plasma systems used in advanced manufacturing, with industrial collaboration from Oxford Instruments.
Project Description
Low-temperature plasmas are essential for advanced manufacturing applications, but their design and control remain challenging. This project will:
Develop numerical simulations of plasma processes.
Perform optimisation studies for plasma systems.
Explore machine-learning-based surrogate models to accelerate system design and control.
The research combines computational modelling, data-driven methods, and applied physics to support advanced manufacturing process optimisation.
Entry Requirements
Background or strong interest in engineering, physics, applied mathematics, computational modelling, or data science
How to Apply
More details and application via: University of Exeter Funding Page
Eligibility
UK/Home
EU
International
Supervisor Profile
DH
Dr Hussein Rappel
The University of Exeter, College of Engineering, Mathematics and Physical Sciences
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