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Centre for Doctoral Training in Financial Computing & Analytics

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The PhD in Financial Computing offers a unique opportunity to gain the skills and contacts required for work in the financial services industry. Competition for places is high, and students must achieve excellent academic qualifications in order to be selected for the course and secure funding.

Once on the course, students work proactively together - particularly in the first year when they participate in seminars, attend reading groups and other activities, and share workspace with each other. In subsequent years they move to work in different departments within the Centre. Some PhD students lecture to undergraduates on their research during the course.

PhD Student profiles
Explore the specialist research topics, interests and background details of students at the PhD Centre in Financial Computing.
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Photo Details
Georgios Vichos
Risk-sharing games, MCMC
Anna Zaremba
causality, complex networks, time series, machine learning
Mital Kinderkhedia
Natural Language Processing
David Mguni
Stochastic Control Theory and Stochastic Differential Game Theory. Asymmetric Information, Impulse Control Theory.
Leslie Kanthan
Graph Theory, Mathematics, Sublinear
Neil Bramley
Cognitive and formal models of causal structure induction and inference
Annika Birch
Counterparty risk, Systemic risk
Reinhard Fellmann
Systemic Risk, Credit Risk, Asset Pricing
Verena Viskovic
Modelling commodity markets
Bogdan Batrinca
algorithmic trading, trading volume prediction model, strategies analysis, performance decomposition, what-if scenarios

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Industry partners

We have partnerships with 20 leadng financial institutions.

Our PhD programme

Read about our programme structure, training facilities and work expected of Financial Computing PhD students.