If a project does not come with specific funding, that doesn't mean that there is no funding available. Apply to work with a supervisor whose research area you are interested in, and if your application is successful, you may be awarded a scholarship from one of the following sources.
Being offered a place and being offered funding are two separate things. It can take a long time after you are offered a place to find out whether funding is available. After our committee has met to decide on the first round of funding offers, individuals who have been made an offer are given time to consider them. If they decline, the funding may be offered to someone else.
We also accept applications from students who are applying for funding separately, or have funding in place already – please include any details in your application form.
We expect to be able to offer a limited number of scholarships from the Engineering and Physical Sciences Research Council, to start in October 2024.
These scholarships cover home level fees and stipend for 3.5 years, and research training and support. The stipend will be at the standard UKRI rate, which is £18,622 full-time equivalent for the current 2023-24 academic year.
International students are eligible, though the number of studentships they may be allocated is further limited. A university scholarship would make up the difference in fees for International students awarded an EPSRC studentship.
No separate application for this funding is necessary, but to be considered for the first round of funding offers, the usual application form for a place to study should be submitted by 5pm on Wednesday 17th January 2024
This year the Faculty of Science is fully-funding a studentship (including stipend and Home level fees for 3.5 years, and research training support) in the Statistics group, under the supervision of Dr. Wei W. Xing, to start as soon as possible during the 2023-24 academic year. The subject of the research project will be AI for manufacturing and scientific computing. More specifically, the subject will explore the use of modern AI techniques (e.g., Bayesian nonparametric models, deep learning, Bayesian optimization, and reinforcement learning) for improving computation and simulation processes involved in manufacturing and engineering. Examples are digital twins, physics-informed machine learning, and spatial-temporal data predictions.
To be sure of consideration for this funding, please name Dr. Wei W. Xing as a proposed supervisor on your Ph.D. application, and submit that as soon as possible. Students are encouraged to contact him to discuss potential research projects before making an application. You will find information about Dr. Wei W. Xing at wayXing.github.io or wxing.me.
Now closed for applications for October 2023 entry. Please see the link for further details.
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