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HetSys CDT Thesis Library

2025 – Cohort 3

Anis, Geraldine: Dislocation dynamics in Ni-based superalloys.

Fakhoury, Ziad: Graph-driven sampling of protein folding pathway ensembles.

Holroyd, Oscar: Controlling infinite-dimensional nonlinear systems : application to falling liquid films.

Nutter, Matthew: Atomistic modelling of screw dislocation mobility in tungsten with data-driven potentials

Parrag, Matyas: Developing methods to enable high throughput, complex membrane protein simulation workflows.

Rocke, Thomas: Atomistic modelling of defects in indium phosphide with machine learning interatomic potentials.

Siddiqui, Anas: Machine-learned interatomic potentials for two-dimensional transition metal dichalcogenides and their heterostructures.

2024: Cohort 2

Connor Allen Stewart: From first principles to phase diagrams : modelling Ti and its alloys at extreme conditions.

Iain Best: Uncertainty quantification with machine learning interatomic potentials using conformal prediction

Adam Fisher: Modelling the extraordinary strength of superalloys

Joe Gilkes: Chemical reaction discovery with Kinetica.JL : exploration and simulation of chemical degradation

Peter Lewin-Jones: Liquid drop impacts: when trapped gas nanofilms lead to bouncing

Tadashi Matsumoto: Statistical calibration of probabilistic numerical methods for parabolic PDE-constrained inverse problems

Charlotte Rogerson: Investigation of the impact of equation of state models on inertial confinement fusion simulations

Lakshmi Shenoy: Modelling defects in iron and its alloys with machine-learned interatomic potentials

Alisdair Soppitt: The statistics of reactive mixing in rough channels

James M. Targett:The effect of functionalisation on thermoelectric properties of molecular junctions

2023: Cohort 1

Andrew Angus: Probabilistic modelling of stimulated raman back-scatter in laser direct-drive fusion plasmas at ignition scale

Katarina Blow: The role of kinetics, order parameters, and entropy in computing crystallisation rates

Matthew Harrison: Uncertainty quantification and propagation of hydraulic conductivity fields across scales and their effect on flow and solute transport

Idil Ismail: Accelerating chemical reaction discovery using graph-driven searches and machine learning strategies.

Jingbang Liu: Fluctuating hydrodynamics of nanoscale thin films.

Carlo Maino: Machine learned potentials for theoretical spectroscopy of molecules in solvent

Aravinthen Rajkumar: Structure-property relations for block copolymers: a molecular data-driven approach

Christopher Woodgate: Atomic arrangements in multicomponent alloys : first-principles theory, atomistic modelling, and implications for magnetic properties

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