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A fully-funded 3.5-year PhD studentship (covering UK home student fees and an annual stipend of £21,805) is available in Applied Mathematics for Formulated Products. The PhD will be under
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This PhD project will develop mathematical models to investigate population dynamics in biological systems. Combining dynamical systems theory, mathematical modelling, and data-driven approaches
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Application deadline: 30.09.26 Research theme: Applied Mathematics, Thermal-Fluid-Dynamics, Multi-Physics How to apply: https://uom.link/pgr-apply-2425 UK only This 4 year PhD project is fully
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About the project: Multiscale Molecular Dynamics: a mathematical exploration of coarse-graining Supervisor: Dr Thomas Hudson, University of Warwick When applied to molecular dynamics simulations
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4-year PhD fellowship in the Research Programme - Deep Learning-Accelerated Crystallography Pipeline
We welcome applications from candidates with a broad range of academic backgrounds and experiences for a 4-year PhD project on Mathematical and Machine Learning Aspects in Crystallography at Durham
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or Mathematics. Excellent English written and spoken communication skills. It is desirable that candidates possess expertise in some (but not all, or even most) of the following areas: Microbiology, Bacteriology
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new approach has emerged that integrates data and mathematical models through neural networks. This has led to the development of a method for solving partial differential equations (PDEs) known as
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embedded decision-makers who interpret health risks through multiple, often competing, social identities. Traditional epidemic models offer mathematical precision but fail when confronted with this reality
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mathematics. You will undertake a single, ambitious research project: to begin the formalisation of the local Langlands correspondence for GL₂(F) in the Lean interactive theorem prover by leveraging AI agents
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Science, Mathematics, Statistics, or a closely related field Solid grounding in machine learning and/or probability/statistics Programming proficiency in Python and familiarity with ML frameworks (PyTorch, JAX