University of Bristol, UK
Location: Bristol
Degree: PhD in Aerospace Engineering
Funding: Fully funded, standard EPSRC stipend
Study mode: Full-time
Deadline: 4 November 2026
Expected start: No later than March 2027
Project
This PhD will study machine learning methods for controlling high-speed and highly manoeuvrable aerial vehicles.
Research areas include:
• Physics-informed neural networks
• Dynamical systems
• Flight control
• Path planning
• Adaptive guidance and control
• Machine learning for aerospace systems
The project will focus on physics-informed, meta-learned adaptive guidance that can adjust to new targets, atmospheric conditions, or vehicle states using limited real-time measurements.
The project is co-funded by an industrial partner in the defence sector. A work placement with the partner may be available.
Candidate requirements
• 2:1 or above undergraduate degree in STEM
• MATLAB and Simulink skills
• Knowledge of flight control
• Knowledge of dynamical systems
• Machine learning skills
• Relevant academic or industrial experience
Eligibility
Applicants must qualify for UK Home student status and are expected to obtain UK security clearance.
Applicants should confirm their fee status when contacting the supervisors.
How to apply
Apply through the University of Bristol postgraduate application portal.
Website: www.bris.ac.uk/pg-howtoapply
Select “PhD in Aerospace Engineering” on the Programme Choice page. Enter the studentship details in the Funding and Research Details sections.
Contacts
Dr Duc Nguyen
duc.nguyen@bristol.ac.uk
Dr Bahadir Kocer
b.kocer@bristol.ac.uk
Professor Mark Lowenberg
m.lowenberg@bristol.ac.uk