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The University of Manchester
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PhD Studentship in Bayesian Modeling of High-dimensional Structural Data The University of Manchester in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
Oct 28, 2026
Country
United Kingdom
University
The University of Manchester

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About this position
PhD Studentship: Bayesian Modeling of High-dimensional Structural Data at The University of Manchester, Department of Mathematics.
This fully funded PhD project focuses on Bayesian modeling for high-dimensional structural data, with applications across biological sciences, social science, and engineering. The research aims to develop a comprehensive Bayesian learning framework for problems involving underlying covariance structures, conditional dependency graphs, and time-varying high-dimensional structures influenced by latent factors or variables.
The project emphasizes both computationally efficient and scalable methods and the establishment of relevant theoretical properties. This makes it a strong fit for applicants interested in statistics, mathematics, computational science, and data-driven methodology development.
Funding: The studentship is fully funded for 3.5 years for UK/home students. It includes an annual tax-free stipend at the UKRI rate (£21,805 for 2026/27) and tuition fees are covered. The stipend is expected to rise each year.
Eligibility: Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering-related discipline.
How to apply: Contact Dr Nilabja Guha by email with your current level of study, academic background, relevant experience, and a paragraph describing your motivation for the project.
Deadline: 28 October 2026.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
More information can be found here
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