NEW FOR 2018 - Two fully funded Three Year PhD Studentships jointly funded by Royal Holloway University of London (RHUL) and AlgoLabs in: Online Machine Learning for Effective Market Making Pricing and Risk Management Hedging Strategies


Royal Holloway University of London (RHUL) and AlgoLabs


Generous tax-free stipend of £20,000 per year, equipment and research expenses, plus all tuition fees paid at UK/EU rates.

Closes 31/03/2018



AlgoLabs is a global FinTech start-up, born as an R&D subsidiary to its parent companies Divisa Capital Ltd and Equiti Global Markets. The primary objective of AlgoLabs is to research, build and provide support for in-house/proprietary high-level trading software that can effectively provide solutions from front to back for financial brokers. AlgoLabs has unique links to academic institutions, in particular those that relate to STEM subjects, to help drive research into novel trading ideas and models that build on its software, hence its tagline ‘Science of Trading’. One year since its inception, AlgoLabs has now established office space in Bracknell, Berkshire and at Royal Holloway University of London (RHUL) in Egham, Surrey, UK.

AlgoLabs is currently a 10-person team managed by Dr David Lindsay who is a RHUL alumnus and has worked in the finance sector for over 10 years. AlgoLabs is seeking to expand its team by offering two fully-funded and full-time PhD projects based at its RHUL office in Egham. The projects outlined below have been designed and will be co-supervised in conjunction with Professor Chris Watkins and Dr Yuri Kalnishkan from the Department of Computer Science at RHUL. Both projects offer bright and talented graduates the unique opportunity to learn about the fast-paced and exciting world of finance in an exceptional research setting.

For information about working at RHUL, the Computer Science Department, and the Computer Learning Research Centre, please see:


Brief Project Descriptions

The financial marketplace is a huge, ever-growing, complex and extremely exciting venue for trading all sorts of assets, such as Bonds, Equities and FX (Foreign Exchange). In this marketplace there are all kinds of players trading with each other, from individuals to hedge funds, investment and retail banks and even automated trading models. Transactions can be tiny in value (e.g. 10p) or huge (e.g. £100 mio)! To participate in the financial marketplace, one has to either buy or sell something, making money by remembering this main rule - sell high, buy low!

AlgoLabs has developed its own proprietary software suite which are fully automated data driven models designed to run the full lifecycle of the business: from pricing to clients (the pricing model), to managing the resulting risk that accumulates (the hedging model) and execution of desired hedges to wider market (the execution model).

Working within this lifecycle, two related yet distinct PhD projects have been planned, both will investigate the use of online machine learning, with the first being focused on online machine learning for effective market making pricing strategies. The second project will investigate online machine learning for effective risk management hedging strategies. Both projects will work with large amounts of historic Foreign Exchange (FX) data (including time-series and price data), and so initially will be focused toward developing pricing and hedging strategies for the FX marketplace.


For information about the company AlgoLabs please refer to


Entry Requirements and Salary

We are looking for two outstanding people with an interest and/or expertise in some of the following fields:

·       Machine Learning

·       Time series Analysis

·       Backtesting Trading Models

·       Online Predictive Analytics

·       Complex Event Processing

·       Quantitative Finance

·       Deep Q-Learning (especially applications building agents to play games)

·       Recurrent Neural Networks, LTSM

·       Reinforcement learning

·       High Frequency Trading

·       Market Making

·       Real Time Systems

·       Portfolio Risk Optimisation

·       Knowledge of Foreign Exchange and CFD markets

·       Prediction with expert advice

·       Prediction with confidence

Applicants should possess or be expected to receive a good (1 or 2.1) honours degree in Computer Science/Mathematics or other relevant STEM discipline. It is essential that applicants are strong programmers in a suitable object-oriented programming language.

Candidates must also be able show that their English language proficiency is at a level which allows them to successfully complete the PhD. All applicants require an English language qualification, typically a GCSE or an IELTS test (a score of 7 or above is required, with a minimum of 6 in each component).

The award provides each PhD student with a generous stipend of £20,000 p/a and includes a top-spec laptop for data analysis and an allowance of £3,000 p/a for research/travel expenses.

Note: due to RHUL sponsorship requirements, these projects are open only to UK and EU applicants.


Start date: 03 September 2018

Duration: 3 years

Applications deadline: 31 March 2018


How to Apply

To apply, please send in a covering letter and your CV to

In your covering letter please explain how you meet some or all of the eligibility criteria as outlined above and what interests you about the PhD projects. If you have any questions about any aspect of the PhD projects please email