How the programme works
All QRT Labs PhD students at Imperial are registered in the Department of Computing and supervised from a pool that spans Computing, the Department of Mathematics and the Business School. A project need not be interdisciplinary. But when it does not fit within one discipline, students are encouraged to seek advice from the other departments and to take courses across them.
The training is built around the project rather than a fixed curriculum. Depending on the project, a student may need the mathematics of the markets they are building for, the engineering that makes the code running their models reliable, or the economics that explains what a market is doing and why. Each is taught in a different department.
Courses across Imperial
A selection of the advanced modules students draw on, by department. None of them is compulsory and there are no exams: PhD students audit the courses their project needs, attending the lectures without being assessed. Students are also encouraged to apply for teaching assistant positions on the courses whose material they know well.
Select an example path to see how one PhD reaches across all three departments.
Three example paths
Computing
- Advanced Computer Security
- Cryptography Engineering
- Privacy Engineering
- Scalable Systems and Data
- Scalable Software Verification
- Program Analysis
- Software Reliability
- Deep Learning
- Reinforcement Learning
- Hardware and Systems for Machine Learning
Mathematics
- Stochastic Processes
- Quantitative Risk Management
- Statistical Methods for Finance
- Computing for Finance
- Numerical Methods in Finance
- Market Microstructure
- Quantitative Trading and Price Impact
- Stochastic Control in Finance
- Generative Modelling in Finance
- Optimisation in Machine Learning
Business School
- Decision Making Under Uncertainty
- Econometrics
- Asset Pricing Theory
- Empirical Asset Pricing
- Corporate Finance
- Optimisation
- Machine Learning for Analytics
- Machine Learning and Text Analysis for Social Science
- Topics in Empirical Banking
A PhD on the security of low-latency distributed systems: making them resist adversaries and faults without slowing them down. Systems security and cryptography come from Computing, the probability needed to reason about failure and risk from Mathematics, and from the Business School an understanding of how decisions are made under uncertainty and what an attack actually costs.
Advanced Computer Security · Cryptography Engineering · Privacy Engineering · Scalable Systems and Data · Stochastic Processes · Quantitative Risk Management · Decision Making Under Uncertainty
A PhD on verifying that numerical and machine-generated code does what its specification says, including meeting a performance budget. Verification and program analysis come from Computing, the numerical methods the code implements from Mathematics, and optimisation from the Business School to state precisely what the code is meant to be good at.
Scalable Software Verification · Program Analysis · Software Reliability · Computing for Finance · Numerical Methods in Finance · Optimisation
A PhD on learning from market data at scale: models that predict, trade and stay robust when the market changes. Deep and reinforcement learning and the hardware that runs them come from Computing; microstructure, price impact and stochastic control from Mathematics; and empirical asset pricing from the Business School, so that a signal is understood and not only found.
Deep Learning · Reinforcement Learning · Hardware and Systems for Machine Learning · Market Microstructure · Quantitative Trading and Price Impact · Stochastic Control in Finance · Generative Modelling in Finance · Empirical Asset Pricing · Machine Learning for Analytics
Beyond courses
QRT Labs runs shared seminars and an annual conference across the Imperial, Cambridge and Oxford centres, with researchers from QRT. Students are encouraged to take internships during the PhD, at QRT or at any other technology organisation they are interested in.
Students are also encouraged to follow the seminar series relevant to their project. Among those at Imperial, in London and at Oxford:
- Finance Seminars, Imperial Business School
- CFM-Imperial Quantitative Finance Seminar
- Finance and Stochastics, Department of Mathematics
- Control and Optimisation Seminars, Department of Mathematics
- London Mathematical Finance Seminar
- Frontiers in Quantitative Finance Seminar, Mathematical Institute, Oxford
Apply
How to apply, funding and deadlines are on the Admissions page.