Our co-designed projects are developed jointly by academics in the Department of Mathematical Sciences and partner collaborators, and bring interesting, fresh perspectives to challenges in organisations and other disciplines. The projects are often developed from our Integrative Think Tanks.
SAMBa students working on a partner project join the SAMBa cohort and build towards their PhD research during the first nine months by undertaking a series of courses, training opportunities and projects alongside their peers. Have a look at the SAMBa Programme page for more details.
The medical imaging technique Positron Emission Tomography (PET) is an important cornerstone in modern medicine allowing non-invasive, sensitive, and specific detection of disease. Small metastases at the edge of the PET resolution limit are difficult to correctly diagnose with the current technology. In this PhD project, we are investigating Bayesian inference, backed by sound mathematical and statistical theory to tackle this problem.
Adaptive designs for clinical trials add flexibility to the clinical development process, using pre-planned interim analyses to allow alterations to the trial in progress. This research, conducted in close collaboration with project partners at Novartis, explores the problem of inference after a trial with an adaptive design.
This project aims to develop a rigorous, data-informed mathematical formalism to represent, propagate and mitigate uncertainty in radiotherapy, drawing on tools from probability, statistics, optimisation and PDE-constrained inverse problems.
Having an industry partner for my PhD has benefitted me a lot. It’s nice having those outside links but also that different perspective. My collaborators have both worked for other companies before CEA and bringing that kind of expertise into the project is fantastic.
Automatic diagnosis of psoriasis arthritis (xAPAD)
Adwaye Rambojun
Optimisation of wireless router location
Hayley Wragg
Finite element methods for Boltzmann neutron transport equation on polygonal and polyhedral meshes
Matt Evans
Adaptive Undersampling in Spectromicroscopy
Oliver Townsend
Optimising Psychological Treatment in the NHS
Adeeb Mahmood
Raising the Roof: Extension of the Met Office’s Unified Model into the Mesosphere and Lower Thermosphere
Matthew Griffith
The role of precursors of active regions in space weather forecasting
Tina Zhou
Phase 3 clinical trial statistics
Abigail Burdon
Mathematical and Statistical Analysis of time series data to quantify trends and events in ocean noise
Gianluca Audone
Exploring adaptive enrichment in clinical trials
Sam Williams
Seamless and overarching approaches for optimizing over the phases of drug development
Robbie Peck
Optimising First in Human Trials
Lizzi Pitt
Modelling of ice crystal icing in engines
Timothy Peters
On-line drill system parameter estimation and hazardous event detection
Dan Burrows
Mathematical and numerical problems in seismic imaging
Shaunagh Downing
Bayesian inference for low-resolution Nuclear Magnetic Resonance in porous media
Michele Firmo
Mathematical modelling of formulation composition trade-offs for pesticides
Jenny Delos Reyes
Monte Carlo methods for the neutron transport equation via branching processes
Emma Horton
