networks. In all these cases, the parametrization is typically irregular, meaning that the occurring linear systems are generally ill-conditioned.
The project sits at the intersection of classical numerical analysis, scientific machine learning and computational chemistry. Based on regularization techniques and time-stepping schemes applied to gradient systems, the project aims to contribute towards the treatment of high-dimensional optimisation problems, such as the electronic structure problem.
We are looking for a highly enthusiastic and motivated student with
- a strong 1st class degree in Mathematics at the MMath/MSci/MSc level, or equivalent;
- a solid background in numerical analysis of differential equations;
- excellent programming skills;
- excellent communication skills (oral and written).
Informal inquiries should be directed to Dr Jörg Nick, e-mail: j.a.nick@bham.ac.uk
Funding notes:
Funding may be available through a college or EPSRC scholarship in competition with all other PhD applications.
The scholarship will cover tuition fees, training support, and a stipend at standard rates for 3.5 years.
Early application is strongly recommended; there is an annual deadline (typically at the end of January) for scholarship applications; however, later applications may also be considered. Applications of overseas candidates can only be considered until the beginning of September. Strong self-funded applicants worldwide will also be considered.
Strong candidates are encouraged to make an informal inquiry at j.a.nick@bham.ac.uk.
References:
https://link.springer.com/article/10.1007/s00211-026-01551-5
