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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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Oliver Rice
Algorithmic Trading; Machine Learning; Multi-objective Optimization
Marc Sloan
Information Retrieval, Reinforcement Learning, Portfolio Theory
Johannes Heinrich
Reinforcement Learning, Computational Game Theory
Pascal Khoury
Volatility, Trading Models
Mahnoosh Mirghaemi
Bayesian Learning, Econometrics, HFT.
Lukasz Kopec
Decision making
Andrew McDonald
Machine learning, bayesian statistics
Blaz Zlicar
Computational Finance
Oliver Rice
Optimal Portfolio Selection
Noemi Nava
pricing derivatives, interest rate models

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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.