Project Overview
About the Position
This project focuses on developing a comprehensive Bayesian learning framework for high-dimensional structural data with practical applications.
| Opportunity | Fully Funded PhD Studentship: Bayesian Modeling of High-Dimensional Structural Data |
| Host | University of Manchester |
| Location | Manchester, United Kingdom |
| Study Level | PhD |
| Funding | Fully Funded, stipend provided, tuition covered |
| Stipend | £21,805 per year (tax-free, UKRI rate for 2026/27) |
| Application Deadline | Deadline not confirmed: imported dates conflict (28 October and 31 December 2026). Confirm with Manchester before applying. |
| Apply | Official application page ↗ |
Deadline to Confirm
The imported record contains conflicting closing dates. Confirm the current deadline and availability directly with the university before applying; this listing does not establish a submission time.
Basic Information
- Full Project Title: PhD Studentship: Bayesian Modeling of High-dimensional Structural Data
- Host Institution: The University of Manchester
- Department: Department of Mathematics
- Supervisor: Dr Nilabja Guha
- Study Level: PhD
- Duration: 3.5 years
- Start Date: October 2026
- Funding Type: Fully Funded
- Stipend: £21,805 per year (tax-free, UKRI rate for 2026/27)
- Tuition Fees: Covered
- Eligibility: Home students (UK) only
- Application Deadline: 28 October 2026 (all year round)
Project Description
In many applications such as biological sciences, social science, and engineering, we encounter high-dimensional observations. Bayesian approach can provide a flexible modeling framework for underlying structures in high dimension such as underlying covariance structure, conditional dependency graphs etc. With the change in data-generating mechanism, these high-dimensional structures may change with time, where the change can depend on latent factors or variables. These projects will focus on developing a comprehensive Bayesian learning framework for this broad class of problems while focusing on specific applications. The goal would be to develop computationally efficient and scalable Bayesian learning methodologies with practical applications and establish relevant theoretical properties.
Requirements
- At least a 2.1 honours degree or a Master's (or international equivalent) in a relevant science or engineering-related discipline
Contact
Questions about this position, eligibility or the application process should be sent to the contacts above or raised through the channel given on the official announcement page.
Official Link
Full announcement and application portal: https://www.se.manchester.ac.uk/study/postgraduate-research/getting-started/applying/
Source: se.manchester.ac.uk - the details in this listing were recorded from this official page.
Important Notes
- Application deadline: 31 December 2026 - late or incomplete applications are normally not considered.
- Listing details were recorded from the official source at the time of publication; always confirm the latest requirements on the official page before applying.
- Prepare the documents listed in the eligibility and application sections before starting the online form - transcripts, CV and references take the longest to collect.
About University of Manchester
The University of Manchester is a public research university in Manchester, England, and a member of the Russell Group. It offers undergraduate, master's and doctoral programmes across engineering, science, medicine, business and the humanities. Its research community connects academic discovery with challenges in health, sustainability, technology and society through collaboration.
Official website: https://www.manchester.ac.uk/
How to Apply
Contact Dr Nilabja Guha (nilabja.guha@manchester.ac.uk). Please include details of your current level of study, academic background, any relevant experience, and a paragraph about your motivation to study this PhD project. Apply early as the advert may be removed before the deadline.
Application guides
Frequently asked questions
Drawn from this listing's own record. Always confirm the details on the official source before applying.
What is the deadline for Fully Funded PhD Studentship: Bayesian Modeling of High-Dimensional Structural Data?
The application deadline is 28 October 2026. Applications received after that date are not considered, so treat it as a hard cut-off (Europe/London time) and leave time for references and transcripts. Closing time not specified — confirm with the provider before you leave it until the last day: the source names Europe/London but gives no clock time.
Is Fully Funded PhD Studentship: Bayesian Modeling of High-Dimensional Structural Data fully funded?
This is a fully funded award: tuition is covered and a living stipend is provided for the duration of the programme. £21,805 per year (tax-free, UKRI rate for 2026/27).
Who is eligible to apply for Fully Funded PhD Studentship: Bayesian Modeling of High-Dimensional Structural Data?
This listing is open to UK applicants only. If you are applying from outside the UK, this one will not accept your application — filter United Kingdom listings by residency before you spend time on it. Applications are assessed by University of Manchester.
How do I apply for Fully Funded PhD Studentship: Bayesian Modeling of High-Dimensional Structural Data?
Applications for Fully Funded PhD Studentship: Bayesian Modeling of High-Dimensional Structural Data are submitted directly to University of Manchester through the provider's own application portal — use the Apply button on this page to open it. NextApply does not process applications or charge a fee.
Is an English proficiency test required for Fully Funded PhD Studentship: Bayesian Modeling of High-Dimensional Structural Data?
Yes — an English-language certificate is required for this listing. Check the exact band expected on the official source, since it can differ by programme. Requirements for United Kingdom are published by the provider.
What study level does Fully Funded PhD Studentship: Bayesian Modeling of High-Dimensional Structural Data offer?
This listing is offered at PhD level. That describes the qualification on offer, not a credential you must already hold — check the provider's stated entry requirements before applying.
Similar opportunities
- PhD Real-Time Urban Wind Simulation & Data Reduction for Environmental Hazard AssessmentUniversity of Salford · United Kingdom
- PhD Students in Statistics: Next-Generation Latent Variable Models (Fully Funded 4 Years) - Umea University, SwedenUmeå University · Sweden
- PhD-TA in Statistics (Functional Data Analysis) - Eindhoven University of Technology (TU/e), NetherlandsEindhoven University of Technology · Netherlands
- EPSRC FIBE3 CDT Fully Funded MRes + PhD at the University of CambridgeUniversity of Cambridge · United Kingdom