Mathematics and Computer Science MSc

This interdisciplinary Masters degree provides you with a broad background in some mainstream and modern aspects of mathematics and computer science. You'll be introduced to sophisticated techniques at the forefront of both disciplines.

The programme combines teaching and research from the School of Mathematics and the School of Computing. Based on the Schools' complementary research strengths the programme follows two main strands:

- Algorithms and complexity theory
- Numerical methods and parallel computing

You'll have the choice to specialise in one of these strands, gaining specialist knowledge and skills that will prepare you for a wide range of careers. You'll also develop your research skills when you complete your dissertation.

If you do not meet the full academic entry requirements then you may wish to consider the Graduate Diploma in Mathematics. This course is aimed at students who would like to study for a mathematics related MSc course but do not currently meet the entry requirements. Upon completion of the Graduate Diploma, students who meet the required performance level will be eligible for entry onto a number of related MSc courses, in the following academic year.

  • Course content

    It is expected that you will specialise in one of two areas during the course, although this is not essential.

    The two strands are:

    Algorithms and complexity theory and connections to logic and combinatorics

    This concerns the efficiency of algorithms for solving computational problems, and identifies hierarchies of computational difficulty. This subject has applications in many areas, such as distributed computing, algorithmic tools to manage transport infrastructure, health informatics, artificial intelligence, and computational biology.

    Numerical methods and parallel computing

    Many problems in mathematics, physics, astrophysics and biology cannot be solved using analytical techniques and require the application of numerical algorithms for progress. The development and optimisation of these algorithms coupled with the recent increase in computing power via the availability of massively parallel machines has led to great advances in many fields of computational mathematics. This subject has applications in many areas, such as combustion, lubrication, atmospheric dispersion, river and harbour flows, and many more.

    Course structure

    These are typical modules/components studied and may change from time to time. Read more in our Terms and conditions.

    Year 1

    Optional modules

    • Machine Learning 10 credits
    • Combinatorial Optimisation 10 credits
    • Graph Algorithms and Complexity Theory 10 credits
    • MSc Project 60 credits
    • Bio-Inspired Computing 15 credits
    • Algorithms 15 credits
    • Advanced Distributed Systems 15 credits
    • Parallel and Concurrent Programming 15 credits
    • Mobile Application Development 15 credits
    • Knowledge Representation and Machine Learning 15 credits
    • Data Mining and Text Analytics 15 credits
    • Cloud Computing 15 credits
    • Semantic Technologies and Applications 15 credits
    • Image Analysis 15 credits
    • Scientific Visualization 15 credits
    • Scheduling 15 credits
    • Scientific Computation 15 credits
    • Graph Theory: Structure and Algorithms 15 credits
    • Philosophy of Logic and Mathematics 20 credits
    • Graph Theory 15 credits
    • Number Theory 15 credits
    • Groups and Symmetry 15 credits
    • Proof and Computation 15 credits
    • Differential Geometry 15 credits
    • Models and Sets 15 credits
    • Combinatorics 15 credits
    • Coding Theory 15 credits
    • Algebras and Representations 15 credits
    • Metric Spaces 15 credits
    • Hilbert Spaces and Fourier Analysis 15 credits
    • Topology 15 credits
    • Transformation Geometry 15 credits
    • Hamiltonian Systems 15 credits
    • Mathematical Methods 15 credits
    • Linear and Non-Linear Waves 15 credits
    • Hydrodynamic Stability 15 credits
    • Quantum Mechanics 15 credits
    • Dynamical Systems 15 credits
    • Nonlinear Dynamics 15 credits
    • Analytic Solutions of Partial Differential Equations 15 credits
    • Introduction to Entropy in the Physical World 15 credits
    • Geophysical Fluid Dynamics 15 credits
    • Astrophysical Fluid Dynamics 15 credits
    • Numerical Methods 10 credits
    • Modern Numerical Methods 15 credits
    • Discrete Systems and Integrability 15 credits
    • Actuarial Mathematics 1 15 credits
    • Actuarial Mathematics 2 15 credits
    • Cosmology 10 credits
    • Mathematical Biology 15 credits
    • Evolutionary Modelling 15 credits
    • Fluid Dynamics 2 15 credits
    • Linear Regression and Robustness 15 credits
    • Statistical Theory 15 credits
    • Stochastic Financial Modelling 15 credits
    • Multivariate Analysis 10 credits
    • Time Series 10 credits
    • Bayesian Statistics 10 credits
    • Generalised Linear Models 10 credits
    • Introduction to Statistics and DNA 10 credits
    • Dissertation in Mathematics 60 credits
    • Linear Analysis 1 20 credits
    • Philosophy of Logic and Mathematics 20 credits
    • Advanced Proof and Computation 20 credits
    • Advanced Differential Geometry 20 credits
    • Advanced Models and Sets 20 credits
    • Advanced Coding Theory 20 credits
    • Fields and Galois Theory 20 credits
    • Commutative Algebra and Algebraic Geometry 20 credits
    • Models in Actuarial Science 15 credits
    • Advanced Hamiltonian Systems 20 credits
    • Advanced Mathematical Methods 20 credits
    • Advanced Linear and Nonlinear Waves 20 credits
    • Advanced Hydrodynamic Stability 20 credits
    • Advanced Quantum Mechanics 20 credits
    • Advanced Dynamical Systems 20 credits
    • Advanced Nonlinear Dynamics 20 credits
    • Advanced Entropy in the Physical World 20 credits
    • Advanced Geophysical Fluid Dynamics 20 credits
    • Advanced Astrophysical Fluid Dynamics 20 credits
    • Advanced Modern Numerical Methods 20 credits
    • Advanced Discrete Systems and Integrability 20 credits
    • Advanced Mathematical Biology 20 credits
    • Advanced Evolutionary Modelling 20 credits
    • Linear Regression and Robustness and Smoothing 20 credits
    • Statistical Learning 15 credits
    • Multivariate and Cluster Analysis 15 credits
    • Time Series and Spectral Analysis 15 credits
    • Bayesian Statistics and Causality 15 credits
    • Generalised Linear and Additive Models 15 credits
    • Independent Learning and Skills Project 15 credits
    • Statistical Computing 15 credits
    • Statistics and DNA 15 credits
    • Show more

    For more information on typical modules, read Mathematics and Computer Science MSc in the course catalogue

    Learning and teaching

    Teaching is carried out through a mixture of lectures and smaller group activities such as workshops. Most modules are assessed by a mix of coursework and written examinations. There is also the opportunity to complete a summer project which is individually supervised by a member of staff.

    Assessment

    The taught course is primarily assessed by end-of-semester examinations with a small component of continuous assessment. The semester three project is assessed by a written dissertation and a short oral presentation.

  • Applying, fees and funding

    Entry requirements

    A BSc degree with a 2:1 (hons) in mathematics or computer science (with a substantial mathematics component), or equivalent. We will also consider students who hold other degrees with a substantial mathematics component.

    We accept a range of international equivalent qualifications.

    English language requirements

    IELTS 6.5 overall, with no less than 6.0 in all components. For other English qualifications, read English language equivalent qualifications.

    Improve your English

    If English is not your first language, you may be able to take a pre-sessional course before you begin your studies. This can help if you:

    • don't meet the English language requirements for your course or
    • want to improve your understanding of academic language and practices in your area of study.

    Our pre-sessional courses are designed with a progression route to the degree programme and are tailored to the subject area. For information and entry requirements, read Language for Science (6 weeks) and Language for Science: General Science (10 weeks). 

    How to apply

    Application deadlines

    31/07/18 - International

    31/08/18 - Home/EU

    • Apply

    This link takes you to information on applying for taught programmes and to the University's online application system.
     
    If you're unsure about the application process, contact the admissions team for help.

    Documents and information you'll need

    Original or certified copies of your transcripts

    Original or certified copies of your degree certificate

    Copy of passport (if applicable)

    Letter of sponsorship (if applicable)

    Names of two academic references

    Original or certified copy of your IELTS/TOEFL results (if applicable)

    It may help your application if you include a personal statement and CV.

    Read about visas, immigration and other information in International students. We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.

    Admissions policy

    Faculty of Mathematics and Physical Sciences Taught Postgraduate Admissions Policy

    Fees

    UK/EU: £10,000 (total)

    International: £21,000 (total)

    Read more about paying fees and charges.

    For fees information for international taught postgraduate students, read Masters fees.

    Additional cost information

    There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more about additional costs

    Scholarships and financial support

    If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government.  Find out more at Masters funding overview.

    The School of Mathematics offers a range of scholarships for UK, EU and International students.

    Find out more about our Scholarships.

  • Career opportunities

    This MSc will provide you with both technical and transferrable skills. It will also offer you excellent preparation for doctoral research in mathematics or computer science or related subjects. On completion of the degree you can progress onto a wide range of opportunities including:

    - PhD in Mathematics, or in Computer Science

    - Careers in Computing and Industries which require algorithmic tools, such as transport infrastructure, health informatics, computational biology, artificial intelligence, Internet-related services and products (e.g. search engines).

    - Many other careers (e.g. in Finance) where a mathematics background is valued.

    In collaboration with both industrial and academic partners, our research has resulted in computational techniques, and software, that has been widely applied. Our industry links are extensive and include companies such as Google, Yahoo, Akamai, Microsoft, and Tracsis, as well as the NHS.

    Careers support

    We encourage you to prepare for your career from day one. That's one of the reasons Leeds graduates are so sought after by employers.

    The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.

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  • MSc Award
    September Start
    Full-time Study Mode
    12 months Duration

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