Before applying to the DAMTP PhD you are encouraged to discuss informally with possible supervisors. It will help our consideration of your application to know with whom you are interested in working and in what fields. This does not necessarily have to be narrowed down to a single supervisor or research area.
Contact details may be found on each supervisor's webpage. You are encouraged to make initial contact by email, and to provide a CV and brief explanation of your areas of interest.
Applied and Computational Analysis (including CMI)
Astrophysics
Fluid Mechanics, Geophysics, Biophysics and Soft Matter
Machine Learning (fundamentals and applications to healthcare)
Quantum Information
Mathematical Biology
High Energy Physics
General Relativity and Cosmology
Applied and Computational Analysis (including CMI)
Supervisor  Interests  Taking students for 2024 

Natalia Berloff  Coherent Quantum systems, quantum and classical neural networks, and physicsinspired computing  Yes 
Maria Bruna  
Colmcille Caulfield  Datadriven methods and high performance computing for climate and environmental science  Yes 
Matthew Colbrook  Foundations of AI, datadriven dynamical systems, spectral problems, PDEs, optimisation  Yes 
Nilanjana Datta  Quantum information theory, in particular, quantum (and classical) entropies and divergences, entanglement theory, quantum channels, hypothesis testing  Possibly 
Hamza Fawzi  Convex optimization and applications to quantum information theory, quantum manybody theory; Semidefinite programming relaxations and sums of squares  Possibly 
Thanasis Fokas  Boundary value problems for linear and integrable nonlinear PDEs; water waves and the SaffmanTaylor problem; inverse problems in medical imaging; the ultrarelativistic limit of the postMinkowskian approximation in general relativity; the large t asymptotics of the Riemann zeta and related functions  Possibly 
Mark Girolami  Computational Statistics, Uncertainty Quantification, Machine Learning  Yes 
Anders Hansen  Functional Analysis, AI, Foundations of Computational Mathematics, Solvability Complexity Index hierarchy and computer assisted proofs, Hardness of Approximation in PDEs, Optimisation and Inverse Problems 
Yes

Duncan Hewitt  Numerical approaches to nonNewtonian fluidflow problems  Yes 
Adrian Kent  Quantum information theory and applications, quantum foundations, quantum theory and gravity, experimental tests  Possibly 
Rich Kerswell  Hydrodynamic stability, transition and turbulence generally (with and without stratification or rotation); viscoelastic (polymer) flows e.g. drag reduction, elastoinertial and elastic turbulence. Machine learning applications to the preceding topics.  Yes 
Chao Li  Developing artificial intelligence and multiomics approaches to better understand brain structure/function and brain disorders  Yes 
Paul Linden  
Nigel Peake  Acoustics, fluidstructure interaction, stability of highspeed flows  
Michael Roberts  Imaging, clinical applications, machine learning  Unlikely 
Carola Schonlieb  Mathematical imaging, inverse problems, applied PDEs, machine learning, optimisation  Yes 
Alexei Shadrin  
Edriss Titi  
Mihaela van der Schaar 
Machine Learning and Artificial Intelligence 
Yes 
Astrophysics
Information for PhD applicants intending to apply to this area is available through this link.
Supervisor  Interests  Taking students for 2024 

Miles Cranmer  Machine learning for astrophysics, turbulence, planet formation, galactic dynamics, galaxy formation, astrostatistics, cosmology  
Giulio Del Zanna  Atomic physics calculations and modelling applied to astrophysical plasma, spectral diagnostic techniques using emission lines to measure the plasma state, and analysis of data of the solar atmosphere from spacebased and groundbased missions  Unlikely 
Henrik Latter  Instabilities, waves, and turbulence in astrophysical settings; Protoplanetary disks and planet formation  Yes 
Gordon Ogilvie  Astrophysical fluid dynamics of discs, planets and stars; waves, instabilities and magnetic fields in rotating fluids; nonlinear dynamics and asymptotic methods  Yes 
Roman Rafikov  Astrophysical fluid dynamics, Accretion discs, Nbody dynamics, Planet formation, Planetary dynamics  Yes 
Fluid Mechanics, Geophysics, Biophysics and Soft Matter
Information for PhD applicants interested in Soft Matter is available through this link.
Information for PhD applicants interested in Solid Mechanics is available through this link.
Information for PhD applicants interested in Waves is available through this link.
Supervisor  Interests  Taking students for 2024 

David Abrahams  
Ronojoy Adhikari  Statistical physics, soft matter physics, continuum mechanics, stochastic processes, Bayesian inference and probabilistic machine learning, numerical solutions of partial differential equations, numerical functional minimisation, epidemiological modelling, applications of machine learning in the digital humanities  Yes 
Lorna Ayton  Wave scattering, asymptotic methods, acoustic metamaterials  Unlikely 
Natalia Berloff  Coherent Quantum systems, quantum and classical neural networks, and physicsinspired computing  Yes 
Rajesh Bhagat  Interfacial flows, building ventilation flow, airborne disease transmission  Yes 
Maria Bruna  
Michael Cates  Statistical physics of soft and active matter  Possibly 
Colmcille Caulfield  Stratified turbulence and mixing, generalized stability theory, environmental and industrial fluid dynamics 
Yes 
Miles Cranmer  Machine learning for fluid dynamics, simulation, surrogate modelling, multiscale physics, astrophysical fluids, planet formation 

Stuart Dalziel  
Giulio Del Zanna  Atomic physics calculations and modelling applied to astrophysical plasma, spectral diagnostic techniques using emission lines to measure the plasma state, and analysis of data of the solar atmosphere from spacebased and groundbased missions  Unlikely 
Stephen Eglen  Computational neuroscience, neuroinformatics  Yes 
Julia Gog  The mathematics of infectious disease  Unlikely 
Ray Goldstein  Biological physics and fluid dynamics, theory and experiment  No 
Anders Hansen  Functional Analysis, AI, Foundations of Computational Mathematics, Solvability Complexity Index hierarchy and computer assisted proofs, Hardness of Approximation in PDEs, Optimisation and Inverse Problems 
Yes

Peter Haynes  
Duncan Hewitt  NonNewtonian fluids, geological and industrial flows, clogging and jamming flows, porous media  Yes 
Robert Jack  Statistical physics, rare events, soft matter, glassy dynamics and metastability  Yes 
Rich Kerswell  Hydrodynamic stability, transition and turbulence generally (with and without stratification or rotation); viscoelastic (polymer) flows e.g. drag reduction, elastoinertial and elastic turbulence. Machine learning applications to the preceding topics.  Yes 
Henrik Latter  Instabilities, waves, and turbulence in astrophysical settings; Protoplanetary disks and planet formation  Yes 
Eric Lauga  Fluid dynamics of living systems; Viscous flows; Complex and nonNewtonian fluids; Active matter; Mathematical modelling of everyday physical phenomena; Physics and mathematics of sports  Yes 
Paul Linden  
John Lister  Stokes flows and lubrication theory, particularly driven by surface tension or with elastic deformation  Possibly 
Gos Micklem  Computational biology  Possibly 
Alison Ming  Coupling between dynamics, radiation and chemistry in the atmosphere with a focus on stratospheric processes  Yes 
Jerome Neufeld  
Gordon Ogilvie  Astrophysical fluid dynamics of discs, planets and stars; waves, instabilities and magnetic fields in rotating fluids; nonlinear dynamics and asymptotic methods  Yes 
Nigel Peake  Acoustics, fluidstructure interaction, stability of highspeed flows  
Roman Rafikov  Astrophysical fluid dynamics, Accretion discs, Nbody dynamics, Planet formation, Planetary dynamics  Yes 
Ben Simons  
John Taylor  Fluid dynamics of the ocean, using numerical simultions, data analysis, analytical techniques  Yes 
Grae Worster  Coupling of fluid mechanics and solidification in geophysical contexts, and the dynamics of hydrogels  Possibly 
Machine Learning (fundamentals and applications to healthcare)
Supervisor  Interests  Taking students for 2024 

Natalia Berloff  Coherent Quantum systems, quantum and classical neural networks, and physicsinspired computing  Yes 
Miles Cranmer  Machine learning for physical sciences, MLaccelerated simulation, foundation models for science (polymathicai.org/), AI for scientific discovery  
Chao Li  Developing artificial intelligence and multiomics approaches to better understand brain structure/function and brain disorders  Yes 
Carola Schonlieb  Mathematical imaging, inverse problems, optimisation, mathematical foundations of machine learning  Yes 
Mihaela van der Schaar 
Machine Learning and Artificial Intelligence (formal applications through the University's Applicant Portal should only be made to work with her once a place has been confirmed), Machine Learning for Healthcare, Machine Learning for Education, RealityCentric AI 
Yes 
Quantum Information
Supervisor  Interests  Taking students for 2024 

Benjamin Beri  Condensed matter theory, topological order, quantum dynamics, quantum computing  Possibly 
Natalia Berloff  Coherent Quantum systems, quantum and classical neural networks, and physicsinspired computing  Yes 
Nilanjana Datta  Quantum information theory, in particular, quantum (and classical) entropies and divergences, entanglement theory, quantum channels, hypothesis testing  Possibly 
Berry Groisman  
Adrian Kent  Quantum information theory and applications, quantum foundations, quantum theory and gravity, experimental tests  Possibly 
Sergii Strelchuk  Quantum computing, quantum algorithms, quantum channels, quantum simulation  Possibly 
Frank Verstraete  Quantum entanglement and its role in manybody physics  Yes 
Mathematical Biology
Supervisor  Interests  Taking students for 2024 

Stephen Eglen  Computational neuroscience, neuroinformatics  Yes 
Julia Gog  The dynamics of infectious disease  Unlikely 
Ray Goldstein  Biological physics and fluid dynamics, theory and experiment  No 
Anders Hansen  Functional Analysis, AI, Foundations of Computational Mathematics, Solvability Complexity Index hierarchy and computer assisted proofs, Hardness of Approximation in PDEs, Optimisation and Inverse Problems  Yes 
Eric Lauga  Biological physics; Physics of cellular processes; Bioengineering; Fluid dynamics of living systems; Transport in biological systems  Yes 
Chao Li  Developing artificial intelligence and multiomics approaches to better understand brain structure/function and brain disorders  Yes 
Gos Micklem  Computational biology  Possibly 
Carola Schonlieb  Mathematical imaging, inverse problems, optimisation, mathematical foundations of machine learning  Yes 
Ben Simons  
Mihaela van der Schaar 
Machine Learning and Artificial Intelligence 
Yes 
High Energy Physics
Supervisor  Interests  Taking students for 2024 

Ben Allanach  HEP phenomenology  Yes 
Alejandra Castro  String Theory, AdS/CFT, and Quantum Gravity  Possibly/Yes 
Nick Dorey  Quantum Field Theory, String Theory and MTheory  No 
Maciej Dunajski  Mathematical Physics, Twistor Theory, General Relativity, Solitons  Yes 
Ron ReidEdwards  Quantum Gravity, String Theory and Quantum Field Theory  Unlikely 
Ben Gripaios  Mathematical approaches to Quantum Field Theory; Theory beyond the Standard Model  Yes 
Sean Hartnoll  Holography, Large Matrices, Quantum Gravity, Quantum Matter  Unlikely 
Alex Mitov  Unlikely  
Enrico Pajer  Quantum field theory in curved spacetime and theoretical cosmology  Yes 
Harvey Reall  General Relativity  Possibly 
Jorge Santos  Exploring diverse facets of general relativity, quantum gravity, gravitational aspects of string theory, and numerical relativity, with a particular focus on studying black holes with antide Sitter asymptotics through field theory considerations  Yes 
David Skinner  Celestial Holography, Topological String Theory, Twistor Theory  
David Stuart  Analysis and Mathematical physics  No 
Christopher Thomas  Lattice QCD and hadron physics  Yes 
David Tong  Quantum field theory  Yes 
Maria Ubiali  Quantum Chromo Dynamics, Machine Learning applications in particle physics phenomenology, Standard Model Phenomenology, Parton Distribution Functions, Standard Model Effective Field Theories, Axions, Heavy quarks  Yes 
Aron Wall  Holographic quantum gravity, black hole thermodynamics, T^2 deformation  Possibly 
Matthew Wingate  Lattice field theory: hadronic matrix elements and weak interactions; novel classical and quantum algorithms  Yes 
General Relativity and Cosmology
Supervisor  Interests  Taking students for 2024 

Anthony Challinor  Constraining fundamental cosmology with the CMB and largescale structure  Possibly 
William Coulton  CMB theory and data analysis, particularly methods to isolate different sky signals and characterize CMB secondaries, and primordial nonGaussianity, both in the CMB and in large scale structure  Possibly 
Miles Cranmer  Machine learning for cosmology and cosmological data analysis, largescale structure, large numerical simulations, simulationbased inference  
Mihalis Dafermos  Proving theorems about general relativity, especially black holes and singularities  Unlikely 
Maciej Dunajski  Mathematical Physics, Twistor Theory, General Relativity, Solitons  Yes 
James Fergusson  Higher order correlation functions of cosmological data sets  Unlikely 
Steven Gratton  Early Universe theory, advanced CMB analysis methods  Possibly 
Sean Hartnoll  Holography, Large Matrices, Quantum Gravity, Quantum Matter  Unlikely 
Christopher Moore  Possibly  
Enrico Pajer  Quantum field theory in curved spacetime and theoretical cosmology  Yes 
Harvey Reall  General Relativity  Possibly 
Jorge Santos  Exploring diverse facets of general relativity, quantum gravity, gravitational aspects of string theory, and numerical relativity, with a particular focus on studying black holes with antide Sitter asymptotics through field theory considerations  Yes 
Paul Shellard  Possibly  
Blake Sherwin  Constraining fundamental physics with CMB and largescale structure  Possibly 
Ulrich Sperhake  Gravitational wave physics, numerical relativity  Unlikely 
Aron Wall  Holographic quantum gravity, black hole thermodynamics, T^2 deformation  Possibly 
Claude Warnick  General relativity, classical field theories, analysis of partial differential equations  Possibly 