Financial Computing and Data Science

About the Centre

The Centre for Doctoral Training in Financial Computing and Data Science was established at University College London (UCL), supported by partnerships with leading financial institutions. It is the first major collaboration between the financial services industry and academia.

The CDT engages academic advisors who are extremely highly regarded and experienced in the field of financial computing and analytics, allowing our PhD students to work with the best supervisors to achieve a deep knowledge of their research subject areas.

Financial Computing and Data Science encompasses a wide range of research areas including Mathematical Modeling in finance, Computational Finance, Financial IT, Quantitative Risk Management and Financial Engineering. PhD research areas include stochastic processes, quantitative risk models, financial econometrics, software engineering for financial applications, computational statistics and machine learning, network, high performance computing and statistical signal processing.

The new UCL CDT coordinates PhD recruitment for Computer Science, Statistics and related departments, offering two types of scholarship:

  • UCL PhD Scholarship – a fully funded 3-year PhD where each student will spend 4 days per week in the department and 1 day with their industry partner.
  • Industry PhD Scholarship – a fully funded 3-year PhD where each student spends 4 days per week with their industry partner and 1 day at UCL. Students will be recruited by the CDT and interviewed jointly with the partner company; or will be company employees who base their PhD research on their job function.

The UCL PhD stipend and fees for 2019 are:


Stipend pa

Fees pa



3-year Total

PhD Home






PhD Overseas






Company employees pay only the fees

We will be pleased to give you advice on the application process, fine-tuning your research project, and help you find a Supervisor and Industry partner:

  1. Email - please send in a single email a copy of your CV and a short (½ page) Research Statement. This is useful in finding a UCL Supervisor.
  2. Academic Supervisor – we recommend strongly finding a PhD Supervisor before applying formally through the UCL web site). You can look at departmental web sites, but we are happy to recommend academics for you to contact.
  3. Industry partners – all PhD students have an industry partner and research collaborator. We will help you find a partner and give you advice. In your email and Research Statement, tell us the type of company and function with which you wish to work.
  4. PhD Application – once you have a Supervisor go to the UCL web site ( and complete the online application listing your target UCL department and Supervisor. For funding, state our CDT. You will also need three reference letters, which can come from your former university and any company for which you have worked.
  5. Advice – we are happy to meet, or speak to you on Skype or the telephone to give advice on your research topic, possible Supervisors and companies, and answer any questions on the application process.

Let us know how we can help you.

Centres for Doctoral Training (CDTs)

In 2007 the Engineering and Physical Sciences Research Council (ESPRC) launched a £250m initiative to create 44 Centres for Doctoral Training (CDTs) across the UK, to train over 2000 doctorate students. Awards were made to universities around the country, and UCL was particularly successful in being awarded nine centres. The current Centre follows the model of the previously EPSRC funded CDT in Financial Computing and Analytics.

CDTs are a bold new approach to training PhD students. They are an initiative widely supported by business and industry. The aim of each centre is to create a community of researchers working on current and future challenges. The multidisciplinary centres bring together diverse areas of expertise to train engineers and scientists with the skills, knowledge and confidence to tackle today’s evolving issues. They also create new working cultures, build relationships between teams in universities and forge lasting links with industry.

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