New starters

More October starters

Vsevolod Chestnov, PDRA in Mathematical Physics, Research Group Mathematical Physics: N1.02

Martin Peev: PDRA in Stochastic Analysis, Research Group Stochastic Analysis: S3.24

November starters

Lukas Waas, PDRA in Topological Data Analysis, Topology: S3.12

Nemanja Draganic, PDRA in Combinatorics, Combinatorics: N3.21

GSA Spark

GSA SPARK 2025 is starting next week!

This is a 21-day challenge from 24th November until 14th December, packed with exciting puzzles and problems inspired by the classic advent calendar. Each day, you’ll tackle new challenges designed to test your maths, coding, and problem solving skills. 

This challenge is for: 

PhD Opportunity at Cardiff University

The School of Mathematics at Cardiff University are advertising a PhD on Monoidal Categories in Mathematical Physics. The project will study monoidal categories (also called tensor categories) and how they can appear as symmetry structures in quantum physics.

Open Research Experiences for Graduates and Undergraduates

The Open Research Experiences for Graduates and Undergraduates (OREGU) program at BAUM TenPers Research Institute is designed for students interested in pursuing a PhD or Master’s in Economics, Finance, Applied Mathematics, Statistics, Financial Engineering, or Financial Mathematics. This tailored remote program offers 1) formal research training and 2) exposure to graduate-level coursework under the guidance of experienced instructors.

Week 6 Student Bulletin

Maths

 

It's the Week 6 Student Bulletin! 

Only two more weeks of Michaelmas term, last push on deadlines before a (hopefully) relaxing break. 

Fri, 13 Mar 2026

11:00 - 12:00
L4

Stop abusing Turing

Dr Thomas Woolley
(Dept of Maths Cardiff University)
Abstract

Everything you have been taught about Turing patterns is wrong! (Well, not everything, but qualifying statements tend to weaken a punchy first sentence). Turing patterns are universally used to generate and understand patterns across a wide range of biological phenomena. They are wonderful to work with from a theoretical, simulation and application point of view. However, they have a paradoxical problem of being too easy to produce generally, whilst simultaneously being heavily dependent on the details. In this talk I demonstrate how to fix known problems such as small parameter regions and sensitivity, but then highlight a new set of issues that arise from usually overlooked issues, such as boundary conditions, initial conditions, and domain shape. Although we’ve been exploring Turing’s theory for longer than I’ve been alive, there’s still life in the old (spotty) dog yet.

Fri, 06 Mar 2026

11:00 - 12:00
L4

Identifiability of stochastic and spatial models in mathematical biology

Dr Alexander Browning
(Dept of Mathematics University of Melbourne)
Abstract
Effective application of mathematical models to interpret biological data and make accurate predictions often requires that model parameters are identifiable. Requisite to identifiability from a finite amount of noisy data is that model parameters are first structurally identifiable: a mathematical question that establishes whether multiple parameter values may give rise to indistinguishable model outputs. Approaches to assess structural identifiability of deterministic ordinary differential equation models are well-established, however tools for the assessment of the increasingly relevant stochastic and spatial models remain in their infancy. 
 
I provide in this talk an introduction to structural identifiability, before presenting new frameworks for the assessment of stochastic and partial differential equations. Importantly, I discuss the relevance of our methodology to model selection, and more the practical and aptly named practical identifiability of parameters in the context of experimental data. Finally, I conclude with a brief discussion of future research directions and remaining open questions.
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