We are a national PhD training centre, covering financial IT, computational finance, analytics, financial engineering and data science. A unique interdepartmental and interfaculty collaboration at UCL .
About the Centre
The Centre for Doctoral Training in Financial Computing and Analytics 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 data science, 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.
Centres for Doctral 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.
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.