Alternative Ways to Fund Your Studies
In today’s climate, it is increasingly difficult to achieve funding for postgraduate research. Many excellent applicants fail to secure funding every year, so if you don’t get funding, it does not invalidate your proposed research. But what can you do to pursue it?
At Warwick, we offer a supportive, flexible environment for postgraduate research, to ensure that as many excellent students as possible can study here whether they have achieved funding or not. If you hold a place here, we would like you to take it up and we hope that the following possibilities might enable you to fund it ‘without full funding’.
Please note we cannot take responsibility for content on external web pages.
Please also refer to individual department webpages for further subject-specific opportunities.
Department of Physics Funded Studentships
Department: Physics
Project: various, covering 6 broad areas of Condensed Matter Physics, Theoretical and Computational Physics, Medical and Biophysics, Astronomy and Astrophysics, Centre for Fusion, Space and Astrophysics and Elementary Particle Physics.
Value: Full payment of tuition fees at the Home rate, a UKRI-rate stipend for 3.5 to 4 years plus additional research costs
Deadline: ongoing
School of Engineering Funded Studentships
Department: School of Engineering
Project: various projects in the key themes of Energy, Biomedical Engineering and Cities
Value: Full payment of tuition fees at the Home rate, a UKRI-rate stipend for 3.5 to 4 years plus additional research costs
Deadline: ongoing
Warwick Manufacturing Group Funded Studentships
Department: Warwick Manufacturing Group
Project: various projects driving innovation in applied science, technology and engineering
Value: Full payment of tuition fees at the Home rate, a UKRI-rate stipend for 3.5 to 4 years plus additional research costs.
Deadline: ongoing
Computer Science - Project Specific Funded Studentship
Department: Computer Science
Title: PhD studentship in the topic of Machine Learning (learning theory or trustworthy machine learning)
Project: We are seeking a PhD candidate in machine learning theory or theoretical-oriented topics (trustworthy ML, efficient ML). The project aims to theoretically understand why ML models perform well and/or design efficient algorithms in trustworthy machine learning. Candidates should have experience in applied mathematics/statistics/computer science. Please contact Dr. Fanghui Liu - fanghui.liu@warwick.ac.uk
Value: Full payment of tuition fees and an annual stipend at the UKRI rate for 3.5 years.
Deadline: 31 December 2024
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