Fully Funded PhD Studentship in Regularized Dynamical Parametric Approximations for Gradient Flows – University of Birmingham, UK

Position Snapshot

• Institution: University of Birmingham, UK

• Department: School of Mathematics

• Level: PhD Studentship

• Location: Birmingham, United Kingdom

• Duration: 3.5 years

• Research area: Dynamical parametric approximations, at the intersection of numerical analysis of partial differential equations and scientific machine learning

• Preferred start date: 1 October 2026 (a later start date can be negotiated)

• How to apply: Online application via jobs.ac.uk (link below)

• Informal inquiries: j.a.nick@bham.ac.uk

About the Position

Applications are invited for a 3.5-year PhD studentship at the University of Birmingham on the topic of dynamical parametric approximations. The project sits at the intersection of numerical analysis of partial differential equations and scientific machine learning — an area concerned with how nonlinear parametrizations, such as neural networks and tensor networks, can be used to numerically approximate evolving systems like gradient flows and other dynamical problems.

This is a mathematically rigorous research direction that bridges classical numerical analysis with modern data-driven modelling techniques, tackling questions such as the stability, accuracy, and regularization of parametric time-integration schemes.

The ideal starting date is 1 October 2026, but a later start date can be negotiated with the supervisor.

Who Should Apply

This studentship will suit candidates with a strong background in mathematics who are interested in:

• Numerical analysis of partial differential equations

• Scientific machine learning and parametric model approximation

• Rigorous, theory-driven research combining analysis with computational experiments

Strong candidates are encouraged to make an informal inquiry before applying.

How to Apply

Full details of the position, including eligibility criteria and formal application instructions, are available on the official job listing:

https://www.jobs.ac.uk/job/DSN395/phd-studentship-regularized-dynamical-parametric-approximations-for-gradient-flows

Strong candidates are encouraged to make an informal inquiry at j.a.nick@bham.ac.uk ahead of applying.

Why This Opportunity Stands Out

This PhD studentship offers:

• A rigorous, well-defined research topic at the intersection of numerical analysis and scientific machine learning — a rapidly growing and highly relevant area of applied mathematics

• The opportunity to work on dynamical parametric approximations, building on recent research into regularized parametric methods for gradient flows and evolution equations

• A fully specified 3.5-year studentship, with flexibility on the start date to accommodate strong candidates

• The chance to engage directly with the supervisor through an informal inquiry, before committing to a formal application

• A base at the University of Birmingham's School of Mathematics, a leading UK centre for research in numerical analysis and applied mathematics

For candidates passionate about the mathematical foundations of scientific machine learning, and who want to work on problems combining rigorous numerical analysis with modern parametric modelling techniques, this is a strong opportunity to pursue doctoral research in a well-supported UK setting.

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