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PhD Studentship: Reinforcement Learning Based Control for Reusable Rockets

University of Bristol - School of Civil, Aerospace, and Design Engineering

Qualification Type: PhD
Location: Bristol
Funding for: UK Students, EU Students
Funding amount: UKRI standard rate (currently £19,237 per annum for 2024/25)
Hours: Full Time
Placed On: 21st August 2024
Closes: 1st October 2024

Funding for:

Home (UK) and EU citizens who have confirmation of UK settlement or pre-settlement status under the EU Settlement Scheme

Funding amount: UKRI standard rate (currently £19,237 for 2024/25)

Hours: Full time

Contract: temporary

Closing date: 01/10/2024

The project:

Rocketry Research, Teaching, and Training (R2T2) is an integrated doctoral programme, run across eight UK universities, which seeks to provide the opportunity to pursue a PhD in space launch technologies. The programme is fully funded, and a budget of approximately £50k will be available to support practical experiments which may include hot-fire, cold-flow, wind tunnel experiments, or similar, according to the needs of the specific project. Where hot-fire is indicated, technical oversight will be put in place and the use of the MachLab test site at Machrihanish Airbase will be offered, although not required. In addition, a practical and online training scheme will be put in place, designed to offer an introduction to the skills required in the space launch industry. These will likely include project management skills, propellant handling, gas/cryogenic safety, and many more. Parts of this training programme will be delivered at Westcott.

This PhD will be based at the University of Bristol as part of the CADE School of Engineering, working in conjunction with Airborne Engineering. The focus of the PhD will be the use of Reinforcement Learning for the active control of rockets for both terrestrial and extra-terrestrial applications. As has been demonstrated by SpaceX, the use of reusable rockets can significantly reduce the cost of launches and can fundamentally change the commercial landscape and what is possible in terms of frequency and payload to orbit.

Building on previous work at Bristol in the development of Reinforcement Learning (RL) for the flight control of drones, this PhD will develop RL based flight control systems for manoeuvring and hovering rockets. For challenging manoeuvres and operations in a diverse range of environments, these offer the potential for a robust and adaptable approach to the control of rocket propelled vehicles.

How to apply:

Prior to submitting an online application, you will need to contact the project supervisor to discuss.

Online applications are made by clicking the 'Apply' button, above.

Please select Aerospace Engineering PhD on the Programme Choice page.

You will be prompted to enter details of the studentship in the Funding and Research Details sections of the form.

Candidate requirements: 

Applicants must hold/achieve a minimum of a merit at master’s degree level (or international equivalent) in a science, mathematics or engineering discipline. Applicants without a master's qualification may be considered on an exceptional basis, provided they hold a first-class undergraduate degree. Please note, acceptance will also depend on evidence of readiness to pursue a research degree.

If English is not your first language, you need to meet this profile level:

Profile E

Further information about English language requirements and profile levels.

Funding:

Funded for 3.5 years by the UK Space Agency.

Fees and minimum tax-free stipend at the current UKRI rate is £19,237 for 2024/25.

For eligibility and residence requirements please check the UKRI UK Research and Innovation website

Contacts:

For questions about the research topic, please contact Thomas.Richardson@bristol.ac.uk.

For questions about eligibility and the application process please contact Engineering Postgraduate Research Admissions admissions-engpgr@bristol.ac.uk

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