PhD Studentship in Geometric Learning and Uncertainty Quantification The University of Edinburgh in United Kingdom

[Full-time PhD tuition fees for Home (£5,006 per annum) or Overseas (£33,100 per annum) students, plus a tax-free stipend at UKRI rate (£20,780 for 2025/26, subject to annual increase) for 3.5 years.]

This fully funded PhD studentship at The University of Edinburgh offers an exciting opportunity to join Dr. Viacheslav Borovitskiy's new research group in the School of Informatics. The primary research focus is on geometric learning and uncertainty quantification, with an emphasis on leveraging the geometry of data to build better models for complex data types such as molecules and images. The position is ideal for candidates interested in machine learning, particularly in exploiting data structure (e.g., symmetries), learning on structured domains (graphs, manifolds), and developing models that quantify their own uncertainty for decision-making and safety-critical applications.

The studentship is fully funded for 3.5 years, covering full-time PhD tuition fees for both Home and Overseas students, and provides a tax-free stipend at the UKRI rate (£20,780 for 2025/26, subject to annual increase). The research group is part of the Institute for Adaptive and Neural Computation, a vibrant community of researchers in machine learning and related fields.

Applicants should have a strong academic background with at least a 2.1 Bachelor's degree or international equivalent, and/or a Master's degree in computer science, mathematics, or a related subject. Proficiency in English and Python programming skills are required, and a solid mathematical background is desirable. Applicants must submit all degree transcripts and certificates (with certified translations if applicable), evidence of English language capability (if required), a short research proposal (max 2 pages), a full CV and cover letter (max 2 pages), and two references. Only complete applications will be considered.

Interested candidates are encouraged to first file an informal application via https://vab.im/vacancies/ to check for mutual interest. Formal applications should be submitted through the University’s admissions portal (EUCLID), selecting the 'Informatics: ANC: Machine Learning, Computational Neuroscience, Computational Biology' programme, and stating the project title and supervisor in the application and research proposal. The application deadline for full consideration is 7 January 2026, with anticipated start dates in May or September 2026. Later start dates may be considered for international applicants requiring additional time for immigration processes.

This position provides a unique chance to shape the direction of a new research group and contribute to the rapidly growing fields of geometric learning and uncertainty quantification. For more information and to apply, visit the official position page.