Financial Computing

Entry requirements

A minimum of an upper second-class UK Bachelor’s degree in a relevant discipline, or an overseas qualification of an equivalent standard. Work experience may also be taken into account.

Months of entry

September

Course content

Challenging and original research projects are undertaken on the PhD programme, with support from the highest standard of academic advisors. Students follow specialist lines of researcg at a doctorate level and apply their work with innovative technologies. Finaincial Computing and Analytics encompasses a wide range of research areas including mathematical modelling in finance, computational finance, financial IT, quantitive risk management and financial engineering. PhD research areas include stochastic processes, quantitive risk models, financial ecometrics, software engineering for financial applications, computational statistics and machine learning, network, high performance computing and statistical signal processing.

Department specialisms

Bioinformatics: protein structure; genome analysis; transmembrane protein modelling; de novo protein design methods; exploiting grid technology; mathematical modelling of biological processes Financial computing: software engineering; computational statistics and machine learning; mathematical modelling Human centred systems: usability of security and multimedia systems; making sense of information; human error and cognitive resilience Information security: cryptology; digital watermarking; cryptoanalysis; steganography Intelligent systems: knowledge representation and reasoning; machine learning Media futures: digital rights management; information retrieval; computational social science; recommender systems Networks: internet architecture; protocols; mobile networked systems; applications and evolution; high-speed networking Programming Principles, Verification and Logic’: logic and the semantics of programs; automated tools for verification and program analysis; produce mathematically rigorous concepts and techniques that aid in the construction and analysis of computer systems; applied logic outreach in AI, security, biology, economics Software systems engineering: requirements engineering; software architecture; middleware technologies; distributed systems; software tools and environments; mobile computing Virtual environments: presence, virtual characters; interaction; rendering; mixed reality Vision and imaging science: face recognition; medical image analysis; statistical modelling of colour information; inverse problems and building mathematical models for augmented reality; diffusion tensor imaging.

Information for international students

Please see: www.ucl.ac.uk/prospective-students/international-students

Fees and funding

Funding opportunities available for students is provided by the UCL Graduate School.
See: www.ucl.ac.uk/prospective-students/scholarships

Qualification and course duration

MPhil

PhD

MRes

Course contact details