Centres for Doctoral Training (CDTs) are one of the three main ways by which EPSRC provides support for Doctoral Training.

EPSRC-funded centres bring together diverse areas of expertise to train engineers and scientists with the skills, knowledge and confidence to tackle today's evolving issues and future challenges. They also provide a supportive and exciting environment for students, create new working cultures, build relationships between teams in universities and forge lasting links with industry.

Congratulations to leaders of the areas in Mathematics who have been awarded grants, and to the teams that helped with the proposals!

Current EPSRC CDTs

Modern Statistics and Statistical Machine Learning (StatML)

Imperial lead: Professor Axel Gandy

StatML is based at Imperial College London and the University of Oxford and aims to train the next generation of leaders in statistics and statistical machine learning, who will be able to develop widely-applicable novel methodology and theory, as well as create application-specific methods, leading to breakthroughs in real-world problems in government, medicine, industry and science. The students’ research will focus on the development of applicable modern statistical theory and methods as well as on the underpinnings of statistical machine learning.

Visit the StatML website >>

Mathematics for our Future Climate: theory, data and simulation

Imperial lead: Professor Dan Crisan

The MFC CDT, a partnership between Imperial College London, University of Reading and University of Southampton. The PhD programme is a dynamic and interdisciplinary initiative that harnesses the power of mathematics to address the urgent issues presented by climate change. It will train 90 highly skilled mathematicians to become future leaders in innovative research, developing environmental prediction technologies, interpreting very large datasets relating to the Earth system, and modelling the risk associated with extreme weather and climate change. Further, they will translate their research into applications in the public and industrial sectors dealing with risk and uncertainty quantification for weather, oceans and climate.

MFC PhD project areas are split into mathematical theory and numerical modelling of fundamental oceanic and atmospheric processes, analysis of data and assimilation with weather and climate models, and mathematical applications related to the response to climate change.

Visit the MFC CDT website >>

Geometry and Number Theory at the Interface

Imperial lead: Professor Alessio Corti

This CDT has been set up in partnership with University College London and Kings College London to help train the next generation of pure mathematicians in the core areas of geometry and number theory. Students will have the opportunity to gain a broad foundation in these fields before undertaking a cutting-edge research project. Additionally, communication and coding skills will be incorporated with teamwork as an integral part of the training. Our graduates will contribute to the sustainability of the mathematical sciences as well as the UK economy more widely. Our centre will also find innovative ways to advance women in mathematics.

Visit the LSGNT website >>

Mathematics of Random Systems

Imperial lead: Dr Tom Cass

A partnership between three world-class departments in the area of probabilistic modelling, stochastic analysis and their applications: the Oxford Mathematical Institute, the Oxford Department of Statistics and the Deptment of Mathematics at Imperial College London. The CDT aims to train the next generation of academic and industry experts in stochastic modelling, advanced computational methods and Data Science, offering a 4-year comprehensive training programme at the frontier of scientific research in Probability, Stochastic Analysis, Stochastic Modelling, stochastic computational methods and applications in physics, finance, biology, healthcare and data science.

Visit the Mathematics of Random Systems website >>

Fluid Dynamics Across Scales

Imperial lead: Professor Demetrios Papageorgiou

This CDT is an Imperial-wide training partnership involving Mathematics and six Engineering departments (Aeronautics, Bioengineering, Chemical, Civil, Earth Science and Mechanical). It spans a wide range of fluid dynamics and is underpinned by three pillars: Aerodynamics, Multiphase flows (including microflows) and Fluid surface/structure interactions. The CDT will train at least 75 PhDs in a unique interdisciplinary environment; students will be trained in theory, scientific computation and experiments, as well as vital transferrable skills of relevance to industry and academia. In addition to cutting-edge research work, students will have industrial exposure through targeted internships with our industrial partners, and will emerge from the programme as the potential future leaders in academic and industrial fluid dynamics research.

Visit the Fluid Dynamics CDT website >>

Financial Computing and Analytics

Imperial lead: Dr Mikko Pakkanen

The Centre for Doctoral Training in Financial Computing & Analytics is a joint venture between Imperial College London, London School of Economics and UCL to promote doctoral training and research on mathematical modeling and computational methods in finance, in liaison with more than twenty financial institutions and industry partners. Students will have the opportunity to take courses across a wide variety of disciplines -mathematics, finance, statistics and computing- and choose from a pool of more than 90 academic supervisors from the Mathematical Finance group in the Deptartment of Mathematics, the Finance Dept at Imperial Business School and other participating institutions.

Visit the Financial Computing CDT website >>

Theory and Simulation of Materials

Imperial lead: Professor Arash Mostofi

The Department also supports the CDT on Theory and Simulation of Materials (TSM-CDT), training a new generation of scientists who have a passion for cutting-edge research and are inspired to use their talent for theory and mathematics to tackle the scientific and technological challenges of today and the future.

Visit the Theory and Simulation of Materials website >>