Scientific Computation is an increasingly important discipline which lies at the interface between mathematics, science and engineering. It is concerned with 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. 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.
The MSc Scientific Computation is designed to reflect the breadth of the subject area and our expertise here at the University of Nottingham. In addition to the core scientific computation modules, 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.
The core modules, taken by all students on the course, provide both 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.
This MSc is taught by internationally-leading experts in the core areas of computational applied mathematics and mathematical modelling. It has been carefully designed to be accessible, not only to mathematicians, but also to anyone with a good first degree in science or engineering. 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.
International Student Satisfaction Awards 2014
Second place ranking
The University of Nottingham has been ranked amongst the top universities in the UK for international student experience.
Nottingham enters the league table at number two in the International Student Satisfaction Awards 2014 and is one of only five UK universities to receive a rating of ‘outstanding’. The rankings are compiled by StudyPortals, an independent study choice platform covering more than 1400 universities in 40 European countries.
This course offers three streams which link with the School of Computer Science and with research groups in Mathematical Medicine and Biology, Industrial and Applied Mathematics (both in the School of Mathematical Sciences).
- The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 60 full-time academic staff.
- In the latest independent research assessment the Research Excellence Framework (REF), the school ranked 8th in the UK in terms of research power across the three subject areas within the School of Mathematical Sciences (pure mathematics, applied mathematics, statistics and operational research).
The MSc Scientific Computation is a full-time degree, studied over a period of approximately 12 months and commencing in late September. The course comprises 180 credits, split between 120 credits of core and optional taught modules and a 60-credit research project. Written and oral presentations will be undertaken at various stages of the course.
The taught modules, which take place during normal semesters, are presented 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
In addition to the taught modules, 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.
We also have regular talks from industrial visitors. Recent talks include:
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, published by 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, also published by 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, published by Springer, where you can examine the basics of chapters 1, 2, 3, 6, 8, 9, 10, 11, 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
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 to view
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.
- 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:
- Guide to Scientific Computing in C++ by J.Pitt-Francis and 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.
or the online tutorial. 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.
There may be slight variations in the lists of optional modules permitted in any particular year.
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++ provides you with the programming skills you will require to implement these algorithms in an efficient manner.
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.
Variational Methods focuses on one of the most powerful and commonly-used techniques in the simulation of science and engineering applications, and uses it to introduce you to formal numerical analysis of algorithms for approximating partial differential equations.
Students must also take 60 credits of optional modules. We suggest that these are restricted to one of the three streams below.
Option Stream 1: Computational Science
Option Stream 2: Mathematical Medicine and Biology
Option Stream 3: Industrial Mathematics/Continuum Mechanics
Information on current course tuition fees can be found on the University finance pages.
The government have announced new postgraduate loans of up to £10,000 for students studying a taught or research masters course commencing in September 2016/17.
These loans will be a contribution towards the costs associated with completing a postgraduate masters course and can be used towards tuition fees or living costs as you decide. The loan is non means tested and will be paid directly to you, the student, rather than the University.
If you are a home student or have UK residential status you will be eligible for a government loan and in some cases EU students may also be eligible.
Full information can be found at the postgraduate loan page on the student services website.
The Graduate School website at The University of Nottingham provides more information on internal and external sources of postgraduate funding.
Information on current course tuition fees can be found on the University finance pages.
International and EU students
The University of Nottingham offers a range of masters scholarships for international and EU students from a wide variety of countries and areas of study.
Applicants must receive an offer of study before applying for our scholarships. Applications for 2016 entry scholarships will open in late 2015. Please note the closing dates of any scholarships you are interested in and make sure you submit your masters course application in good time so that you have the opportunity to apply for them.
The International Office also provides information and advice for international and EU students on financing your degree, living costs, external sources of funding and working during your studies.
Find out more on our scholarships, fees and finance webpages for international applicants.
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 2014, 86.7% of postgraduates in the School of Mathematical Sciences who were available for employment had secured work or further study within six months of graduation. The average starting salary was £25,000 with the highest being £27,000.*
* Known destinations of full-time home and EU postgraduates, 2013/14.
Career Prospects and Employability
The acquisition of a masters degree demonstrates a high level of knowledge in a specific field. Whether you are using it to enhance your employability, as preparation for further academic research or as a means of vocational training, you may benefit from careers advice as to how you can use your new found skills to their full potential. Our Careers and Employability Service will help you do this, working with you to explore your options and inviting you to attend recruitment events where you can meet potential employers, as well as suggesting further development opportunities, such as relevant work experience placements and skills workshops.