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Details of Grant 

EPSRC Reference: EP/S023925/1
Title: EPSRC Centre for Doctoral Training in Mathematics of Random Systems: Analysis, Modelling and Simulation
Principal Investigator: CONT, Professor R
Other Investigators:
Berestycki, Dr J F Reisinger, Professor C Lamb, Professor JSW
Li, Professor X Hambly, Professor B Cass, Dr T
Researcher Co-Investigators:
Project Partners:
Bnp Paribas Capital Fund Management Chinese Academy of Science
Deutsche Bank AG (UK) ETH Zurich InstaDeep Ltd
J.P. Morgan (UK) MedoPad Simudyne Limited
Technology University of Berlin University of Bonn
Department: Mathematical Institute
Organisation: University of Oxford
Scheme: Centre for Doctoral Training
Starts: 01 April 2019 Ends: 30 September 2027 Value (£): 6,626,791
EPSRC Research Topic Classifications:
Mathematical Analysis Numerical Analysis
Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
Healthcare Information Technologies
Financial Services
Related Grants:
Panel History:
Panel DatePanel NameOutcome
07 Nov 2018 EPSRC Centres for Doctoral Training Interview Panel F – November 2018 Announced
Summary on Grant Application Form
Probabilistic modelling permeates all branches of engineering and science, either in a fundamental way, addressing randomness and uncertainty in physical and economic phenomena, or as a device for the design of stochastic algorithms for data analysis, systems design and optimisation. Probability also provides the theoretical framework which underpins the analysis and design of algorithms in Data Science and Artificial Intelligence.

The "CDT in Mathematics of Random Systems" is a new partnership in excellence between the Oxford Mathematical Institute, the Oxford Dept of Statistics, the Dept of Mathematics at Imperial College and multiple industry partners from the healthcare, technology and financial services sectors, whose goal is to establish an internationally leading PhD training centre for probability and its applications in physics, finance, biology and Data Science, providing a national beacon for research and training in stochastic modelling and its applications, reinforcing the UK's position as an international leader in this area and meeting the needs of industry for experts with strong analytical, computing and modelling skills.

We bring together two of the worlds' best and foremost research groups in the area of probabilistic modelling, stochastic analysis and their applications -Imperial College and Oxford- to deliver a consolidated training programme in probability, stochastic analysis, stochastic simulation and computational methods and their applications in physics, biology, finance, healthcare and Data Science. Doctoral research of students will focus on the mathematical modelling of complex physical, economic and biological systems where randomness plays a key role, covering mathematical foundations as well as specific applications in collaboration with industry partners. Joint projects with industrial partners across several sectors -technology, finance, healthcare- will be used to sharpen research questions, leverage EPSRC funding and transfer research results to industry.

Our vision is to educate the next generation of PhDs with unparalleled, cross-disciplinary expertise, strong analytical and computing skills as well as in-depth understanding of applications, to meet the increasing demand for such experts within the Technology sector, the Financial Service sector, the Healthcare sector, Government and other Service sectors, in partnership with industry partners from these sectors who have committed to co-funding this initiative.


This proposal reaches across various areas of pure and applied mathematics and Data Science and addresses the EPSRC Priority areas of (15. Mathematical and Computational Modelling), (22. Pure Mathematics and its Interfaces) ; however, the domain it covers is cross-disciplinary and broader than any of these priority areas taken in isolation. Probabilistic methods and algorithms form the theoretical foundation for the burgeoning area of Data Science and AI, another EPSRC Priority area which we plan to address, in particular through industry partnerships with AI/technology/data science firms.


By training highly skilled experts equipped to build, analyse and deploy probabilistic models, the CDT in Mathematics of Random Systems will contribute to

- sharpening the UK's research lead in this area and training a new generation of mathematical scientists who can tackle scientific challenges in the modelling of complex, simulation and control of complex random systems in science and industry, and explore the exciting new avenues in mathematical research many of which have been pioneered by researchers in our two partner institutions;

- train the next generation of experts able to deploy sophisticated data driven models and algorithms in the technology, finance and healthcare sectors

Key Findings
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Potential use in non-academic contexts
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Date Materialised
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Organisation Website: http://www.ox.ac.uk