Postgraduate study
This course brings together the design, analysis and application of numerical algorithms, which are capable of harnessing the power of high performance computers to simulate complex, real-life events.
MSc Scientific Computation
1 year full-time
Entry requirements
2:2 (or international equivalent) in mathematics or a closely related subject with a substantial mathematics content; some experience with computer programming would be useful
6.0 (no less than 5.5 in each element)

If these grades are not met, English preparatory courses may be available
Start date
UK/EU fees
£9,450 - Terms apply
International fees
£17,910 - Terms apply
University Park Campus



Scientific computation is an increasingly important discipline which lies at the interface between mathematics, science and engineering. Whether you are interested in fundamental scientific research or a technical career in industry, expertise in scientific computation is an invaluable asset.

The mathematical and computational skills required, not only lead to active research fields in their own right, but also provide pathways to a diverse range of potential applications, covering the whole breadth of science and engineering: examples include weather prediction, modelling flow and combustion in a jet engine, and developing optimal treatment strategies for cancer.

What you'll learn

MSc Scientific Computation is designed to reflect the breadth of the subject area and our expertise here at the University of Nottingham.

All students take the core modules. These provide both the theoretical foundations which underpin the design and mathematical analysis of numerical algorithms and the practical skills required to implement them as efficient and robust computer programs.

The optional modules have been selected to broaden your knowledge of scientific computation and of the mathematical models to which it can be applied.

Three streams are suggested in the list of optional modules:

  • Computational Science focuses on the formulation and analysis of fundamental algorithms from the perspectives of both mathematics and computer science.
  • Mathematical Medicine and Biology augments the core material with the development and analysis of models in biomedical mathematics.
  • Industrial Mathematics/Continuum Mechanics draws on the expertise of the Industrial and Applied Mathematics research group in modelling and analysing problems in fluid and solid mechanics.

Key facts

  • One of the largest and strongest mathematics departments in the UK, with over 70 full-time academic staff
  • The Research Excellence Framework (REF) 2014 results place the School in the top 10 nationally within Mathematical Sciences for 'research power' and 'research quality'; with 32% of its research recognised as world-leading and a further 56% as internationally excellent 
  • The research environment was classified as 75% world-leading in vitality and sustainability, with the remaining 25% internationally excellent, reflecting the outstanding setting the school provides for its academic staff as well as its postdoctoral and postgraduate researchers
  • The School scored 87% for Student Satisfaction in the National Student Survey, 2018

Academic English preparation and support

If you require additional support to take your language skills to the required level, you may be able to attend a presessional course at the Centre for English Language Education, which is accredited by the British Council for the teaching of English in the UK.

Students who successfully complete the presessional course to the required level can progress to postgraduate study without retaking IELTS or equivalent. You could be eligible for a joint offer, which means you will only need to apply for your visa once.


Full course details

How you'll be taught

We aim to provide you with a broad set of analytical and computational skills, along with exposure to a range of application areas of both academic and industrial relevance, reflecting the inherently multidisciplinary nature of the subject.

The course comprises 180 credits, split between 120 credits of core and optional taught modules and a 60-credit research project.

  • Taught by internationally-leading experts in the core areas of computational applied mathematics and mathematical modelling
  • Designed to be accessible, not only to mathematicians, but also to anyone with a good first degree in science or engineering
  • Taught modules are in the form of lectures and computer practical sessions, and assessed using a combination of coursework and examinations

The project is a more substantial piece of individual work which develops your ability to engage in independent learning. It is undertaken over the summer under the supervision of a member of academic staff and leads to a written dissertation.

Other skills that you should develop during the course include the ability to think logically and critically, problem-solving expertise, competence in programming and the use of appropriate software, and effective communication of results.

Seminars and industrial speakers

We run both a formal seminar series, in which invited speakers (usually from other universities) present their research, and an informal seminar series in which experts from within the school introduce topics related to their research in a manner accessible to students and researchers in other fields.

Prerequisite information

The MSc Scientific Computation is designed for students with a first degree in mathematics or a related subject with substantial mathematical content (e.g. engineering, physics or computer science). We will assume that your degree has provided you with a basic knowledge of calculus, linear algebra and differential equations.

If you are taking this MSc then you will also need some background in numerical methods, along with enthusiasm and a willingness to learn more about scientific computation, its analysis and its application.

The following two books give an indication of the level of mathematics required:

  • All the Mathematics You Missed (But Need to Know for Graduate School) by Thomas A Garrity (CUP),  covers the required general mathematical background. A basic understanding of the content of chapters 1, 2,3, 5, 12, 13, 14 and 16 would be advisable.
  • An Introduction to Numerical Analysis by Endre Suli and David Mayers (CUP),  covers numerical methods in more detail. You should be able to understand, with some work (reading maths books is never easy!), chapters 1, 2, 6, 7, 11 and 12.

There are many possible alternatives to the second textbook above, all of which describe the relevant background material in numerical methods and scientific computation. These include:

  • Numerical Mathematics by A.Quarteroni, R.Sacco and F.Saleri (Springer), where you can examine the basics of chapters 1, 2, 3, 6, 8, 9, 10, 11 and 13.
  • Numerical Analysis by R.L.Burden and J.D.Faires, published by Brooks/Cole where you can examine the basics of chapters 1-6.

Preparation for Core Modules

Introduction to Finite Element Methods

This is the most mathematically challenging module in the course. It is expected that students taking this module will have knowledge of vector calculus and normed and inner product spaces.

The backgrounds of students taking this module can be diverse, so a more detailed document which details the mathematical concepts with which you should be familiar is available.

Books for module:

  • S. Brenner and R. Scott; The Mathematical Theory of Finite Element Methods (Springer–Verlag, 1994)
  • P.G. Ciarlet; The Finite Element Method for Elliptic Problems (North–Holland, 1978)
  • C. Johnson; Numerical Solution of Partial Differential Equations by the Finite Element Method (CUP, 1990)
  • K. Eriksson, D. Estep, P. Hansbo and C. Johnson; Computational Partial Differential Equations (CUP, 1996)

Scientific Computing and C++

We do not require prior knowledge of C++. You may, however, wish to look through any introductory book on C++ such as the following or follow an online tutorial:

  • Guide to Scientific Computing in C++  by J. Pitt-Francis & J. Whiteley
  • Schaum's Outline of Programming with C++  by J.R. Hubbard
  • Schaum's Outline of Fundamentals of Computing with C++ by J.R. Hubbard

Experience of programming in other languages would be very helpful but not essential.


Computational Applied Mathematics

This module takes place in the second semester, and will build on the analytical and practical skills you acquire in semester one.

It will assume that you have gained enough knowledge of calculus, linear algebra and differential equations to study a broad range of computational algorithms for approximating and solving, numerically, systems of equations.



The structure of the MSc is modular, with individual modules being worth either 20 or 10 credits. One credit represents 10 hours of student work, so a 20-credit module represents 200 hours of study, including formal teaching, independent study, revision, and the preparation of assessments.

The MSc degree requires the successful completion of 180 credits: 120 credits of taught modules, plus a 60-credit scientific computation dissertation.

Core modules

Computational Applied Mathematics

Computational Applied Mathematics introduces you to a broad range of computational methods for solving problems in applied mathematics, showing you how to formulate and analyse different approaches so that you can select and implement the best (in terms of accuracy, efficiency and reliability) approach for solving a given problem.

Scientific Computing and C++

Scientific Computing and C++ provides you with the programming skills you will require to implement these algorithms in an efficient manner.

Scientific Computation Dissertation

The Scientific Computation Dissertation is an individual project which allows you to focus in more detail on an area you have studied that particularly interests you, under the guidance of an expert in that area.

Introduction to Finite Element Methods

Finite element methods are some of the most powerful and commonly-used techniques in the simulation of science and engineering applications, and are used here to introduce you to formal numerical analysis of algorithms for approximating partial differential equations.


Optional modules

Students must also take 60 credits of optional modules. We suggest that these are restricted to one of the three streams below.

Stream one: Computational Science

  • Advanced Techniques for Differential Equations
  • Advanced Algorithms and Data Structures
  • Linear and Discrete Optimisation
  • Software Engineering Management
  • Simulation and Optimisation for Decision Support
  • Parallel and Distributed Computing

Stream two: Mathematical Medicine and Biology

  • Applied Nonlinear Dynamics
  • Mathematical Medicine and Biology
  • Topics in Biomedical Mathematics

Stream three: Industrial Mathematics

  • Advanced Fluid Mechanics
  • Advanced Techniques for Differential Equations
  • Applied Nonlinear Dynamics
  • Elasticity
  • Fluid Mechanic

The above is a sample of the typical modules that we offer but is not intended to be construed and/or relied upon as a definitive list of the modules that will be available in any given year. Due to the passage of time between commencement of the course and subsequent years of the course, modules may change due to developments in the curriculum and information is provided for indicative purposes only.


Fees and funding

UK/EU students

Tuition fees

Information on current course tuition fees can be found on the finance pages.

As a student on this course, we do not anticipate any extra significant costs, alongside your tuition fees and living expenses. You should be able to access most of the books you’ll need through our libraries, though you may wish to purchase your own copies which you would need to factor into your budget.

Graduate School

The Graduate School provides more information on internal and external sources of postgraduate funding.

International students

Tuition fees

Information on current course tuition fees can be found on the finance pages.

School scholarships for UoN UK alumni

For 2019-20 entry, 10% Alumni scholarships may be offered to former University of Nottingham graduates who have studied at the UK campus.

Government loans for masters courses

The Government offers postgraduate student loans for students studying a taught or research masters course. Applicants must ordinarily live in England or the EU. Student loans are also available for students from Wales, Northern Ireland and Scotland.

International and EU students

Masters scholarships are available for international students from a wide variety of countries and areas of study. You must already have an offer to study at Nottingham to apply. Please note closing dates to ensure your course application is submitted in good time.

Information and advice on funding your degree, living costs and working while you study is available on our website, as well as country-specific resources.


Careers and professional development

This course offers a solid grounding in modern scientific computation that will prepare you either for a career in industry or for research in an area where computational methods play a significant role. You will gain experience of the type of problems encountered by academic and industrial researchers, both via taught courses and project work.

Further career information can be found on the School of Mathematical Sciences website.

Average starting salary and career progression

In 2017, 100% of postgraduates in the school who were available for employment had secured work or further study within six months of graduation. The average starting salary was £30,800 with the highest being £60,000.*

* Known destinations of full-time home postgraduates 2016/17. Salaries are calculated based on the median of those in full-time paid employment within the UK.

Career prospects and employability

University of Nottingham is consistently named as one of the most targeted universities by Britain’s leading graduate employers – ranked in the top 10 in The Graduate Market 2013-2019, High Fliers Research.

Those who take up a postgraduate research opportunity with us will not only receive support in terms of close contact with supervisors and specific training related to your area of research, you will also benefit from dedicated careers advice from our Careers and Employability Service.

Our Careers and Employability Service offers a range of services including advice sessions, employer events, recruitment fairs and skills workshops – and once you have graduated, you will have access to the service for life.


This online prospectus has been drafted in advance of the academic year to which it applies. Every effort has been made to ensure that the information is accurate at the time of publishing, but changes (for example to course content) are likely to occur given the interval between publishing and commencement of the course. It is therefore very important to check this website for any updates before you apply for the course where there has been an interval between you reading this website and applying.

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