PhD Studentship: Bayesian Modeling for High-Dim Data

The University of Manchester; Manchester; Hybrid; GBP 18,000 - 20,000; Part time

Job summary

The University of Manchester invites applications for a PhD Studentship: Bayesian Modeling of High-dimensional Structural Data. The project focuses on developing a comprehensive Bayesian learning framework for broad problems in biology, social science and engineering.

Hybrid locations include Birmingham, Bristol, London, Blackburn, Redcar or Doncaster, with the NIoT leading the initiative. Applicants should hold a 2.1 honours degree or Master’s in a relevant science or engineering field.

Qualifications

• Applicants should hold or expect to obtain a 2.1 honours degree or a Master’s (or international equivalent) in a relevant science or engineering discipline.

Responsibilities

• Develop a comprehensive Bayesian learning framework for high-dimensional problems focusing on practical applications.
• Work on scalable computational methods with theoretical properties relevant to the project.
• Collaborate with researchers across disciplines and contribute to academic outputs.

Skills

Bayesian modeling

High-dimensional data

Education

2.1 honours degree or Master’s in a relevant science/engineering field

Job description

The University of Manchester invites applications for a PhD Studentship: Bayesian Modeling of High-dimensional Structural Data. The project focuses on developing a comprehensive Bayesian learning framework for broad problems in biology, social science and engineering.

Hybrid locations include Birmingham, Bristol, London, Blackburn, Redcar or Doncaster, with the NIoT leading the initiative. Applicants should hold a 2.1 honours degree or Master’s in a relevant science or engineering field.