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Scientific Computing and Data Analysis (Financial Technology) at Durham University - UCAS

Durham University

Degree level: Postgraduate

Scientific Computing and Data Analysis (Financial Technology) (Taught)

Course options

2024 - 20252025 - 2026
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Open days

10Feb
Durham University - Postgraduate Online Open Week
Postgraduate

Course summary

Developments in fields such finance, physics and engineering are increasingly driven by experts in computational techniques. The financial services sector has always been at the forefront of data analytics, and those with the skills to write code for the most powerful computers in the world and to process the biggest data sets can give a company a competitive edge. Our suite of Masters in Scientific Computing and Data Analysis (MISCADA) offers an application-focused course to deliver these skills with three interwoven strands:

  • Computer Science underpinnings of scientific computing (algorithms, data structures, implementation techniques, and computer tool usage)
  • Mathematical aspects of data analysis and the simulation and analysis of mathematical models
  • Implementation and application of fundamental techniques in an area of specialisation (as well as Financial Technology we offer options in Astrophysics, Computer Vision and Robotics, or Earth and Environmental Sciences)
The MISCADA specialist qualification in Financial Technology introduces you to the mathematical principles behind modern financial markets, and elements of programming and communication in the context of the financial industry. Financial technology draws on tools from probability theory, statistics and mathematical modelling, and is widely used in investment banks, hedge funds, insurance companies, corporate treasuries and regulatory agencies to solve such problems as derivative pricing, portfolio selection and risk management. There’s great synergy between the modules and you will be given plenty of opportunities to put your learning into practice from the start of the course. Our research-led approach allows you to take some of the newest theoretical ideas and directly translate them into working codes in their respective application areas. If you have an undergraduate degree in a science subject with a strong quantitative element, including computer science and mathematics and want to work at the highest level in financial technology, either in academia or in industry, then this could be the course you’re looking for. Core modules: Introduction to Machine Learning and Statistics provides knowledge and understanding of the fundamental ideas and techniques in the application of data analysis, statistics and machine learning to scientific data. Introduction to Scientific and High Performance Computing provides knowledge and understanding of paradigms, fundamental ideas and trends in High Performance Computing (HPC) and methods of numerical simulation. Professional Skills provides training in areas such as collaborative coding, project management and entrepreneurship. It will build the skill you need to communicate novel ideas in science, and reflect on ethical issues around data and research. The Project is a substantive piece of research into an area of financial technology, scientific computing or data analysis, or a related area in cooperation with an industry partner. The project will develop your research, analysis and report-writing skills. Financial Technology: Algorithmic Trading and Market Making in Options develops your knowledge of financial theory, with a particular emphasis on asset valuation, portfolio management and derivative pricing. In this module you will also develop a critical understanding and appreciation of current research in financial theory and its applications to professional practice. Financial Mathematics introduces the mathematical theory of financial products and provides advanced knowledge and critical understanding of the pricing of financial products and derivatives.

Modules

In recent years optional modules have included: Advanced Statistical and Machine Learning: Foundations and Unsupervised Learning; Advanced Statistics and Machine Learning: Regression and Classification; Data Acquisition and Image Processing; Performance Modelling, Vectorisation and GPU Programming; Advanced Algorithms and Discrete Systems; Computational Linear Algebra and Continuous Systems.

Assessment method

Assessment takes a combination of forms including coursework, presentations and a project which is worth one-third of your total mark. You will complete your dissertation-style project on a topic of your choice from within the contributing academic departments. In the financial technology steam this will usually be Mathematical Sciences or Computer Science, or in close cooperation with on of our industrial partners.

How to apply

International applicants

If you are an international student who does not meet the requirements for direct entry to this degree, you may be eligible to take a pre-Masters pathway programme at the Durham University International Study Centre.

This course has a subject classification which requires students whose nationality is outside the European Economic Area (EEA) or Switzerland to have an ATAS certificate, irrespective of country of residence at the point of application.

Further information can be found on the UK Government's website: www.gov.uk/academic-technology-approval-scheme

Entry requirements

All streams require a UK first or upper second class honours degree (BSc) or equivalent In Physics or a subject with basic physics courses OR In Computer Science OR In Mathematics OR In Earth Sciences OR In Engineering OR In any natural sciences with a strong quantitative element. We encourage applicants to select a specialization area that aligns with their background. Please note that standard business degrees do not provide the necessary mathematical foundation. Additional requirements: Applicants must demonstrate strong programming skills in at least one compiled language, preferably C or C++, although Rust, Java, C#, Fortran, or Pascal are also acceptable. Proficiency in Python may suffice if the applicant has a strong background in their chosen specialization. Those lacking experience in C or C++ are advised to enrol in our pre-sessional course. Additionally we require knowledge of undergraduate-level mathematics, covering linear algebra, calculus, integration, ordinary and partial differential equations, and probability theory. Please see the University guidance for information on required English language levels.

English language requirements

Durham University welcomes applications from all students irrespective of background. We encourage the recruitment of academically well-qualified and highly motivated students, who are non-native speakers of English, whose full potential can be realised with a limited amount of English Language training either prior to entry or through pre-sessional and/or in-sessional courses. It is the normal expectation that candidates for admission should be able to demonstrate satisfactory English proficiency before the start of a programme of study, whether via the submission of an appropriate English language qualification or by attendance on an appropriate pre-sessional course. Acceptable evidence and levels required can be viewed by following the link provided.

English language requirements

https://www.durham.ac.uk/study/international/entry-requirements/english-language-requirements/

Fees and funding

Tuition fees

England £14500 Year 1
Northern Ireland £14500 Year 1
Scotland £14500 Year 1
Wales £14500 Year 1
Channel Islands £14500 Year 1
EU £34000 Year 1
International £34000 Year 1

Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .

Additional fee information

The tuition fees shown are for one complete academic year of study and are set according to the academic year of entry. Fees will be subject to an annual inflationary increase and are expected to rise throughout the programme of study. The fee listed above is for the first year of the course only.

Sponsorship information

For further information see the course listing on the Durham University website.

Scientific Computing and Data Analysis (Financial Technology) at Durham University - UCAS