This one-year master's course provides training in the application of mathematics to a wide range of problems in science and technology. Emphasis is placed on the formulation of problems, on the analytical and numerical techniques for a solution and the computation of useful results.
By the end of the course students should be able to formulate a well posed problem in mathematical terms from a possibly sketchy verbal description, carry out appropriate mathematical analysis, select or develop an appropriate numerical method, write a computer program which gives sensible answers to the problem, and present and interpret these results for a possible client. Particular emphasis is placed on the need for all these parts in the problem solving process, and on the fact that they frequently interact and cannot be carried out sequentially.
The course consists of both taught courses and a dissertation. To complete the course you must complete 13 units.
There are four core courses which you must complete (one unit each), which each usually consist of 24 lectures, classes and an examination. There is one course on mathematical methods and one on numerical analysis in both Michaelmas term and Hilary term. Each course is assessed by written examination in Week 0 of the following term.
Additionally, you must choose at least least one special topic in the area of modelling and one in computation (one unit each). There are around twenty special topics to choose from, spread over all three academic terms, each usually consisting for 12 to 16 lectures and a mini project, which culminates in a written report of around 20 pages. Topics covered include mathematical biology, fluid mechanics, perturbation methods, numerical solution of differential equations and scientific programming.
You must also undertake at least one case study in modelling and one in scientific computing (one unit each), normally consisting of four weeks of group work, an oral presentation and a report delivered in Hilary term.
There is also a dissertation (four units) of around 50 pages, which does not necessarily need to represent original ideas. Since there is another MSc focussed on mathematical finance specifically, the MSc in Mathematical and Computational Finance, you are not permitted to undertake a dissertation in this field.
You will normally accumulate four units in core courses, three units in special topics, two units in case studies and four units in the dissertation. In addition, you will usually attend classes in mathematical modelling, practical numerical analysis and additional skills during Michaelmas term.
In the first term, students should expect their weekly schedule to consist of around seven hours of core course lectures and seven hours of modelling, practical numerical analysis and additional skills classes, then a further two hours of lectures for each special topic course followed. In addition there are about three hours of problem solving classes to go through core course exercises and students should expect to spend time working through the exercises then submitting them for marking prior to the class. There are slightly fewer contact hours in the second term, but students will spend more time working in groups on the case studies.
In the third term there are some special topic courses, including one week intensive computing courses, but the expectation is that students will spend most of the third term and long vacation working on their dissertations. During this time, students should expect to work hours that are equivalent to full-time working hours, although extra hours may occasionally be needed. Students are expected to write special topic and case study reports during the Christmas and Easter vacations, as well as revising for the core course written examinations.
Mathematical models are fundamental to how we understand, analyse and design transportation systems, but these models face challenges from the rapidly changing nature of mobility.
Innovative technologies are being harnessed to deliver new approaches to transport services, and huge volumes of data create new opportunities to examine how patterns of movement are evolving.
If you’re a highly numerate graduate with a desire to apply your quantitative skills to the real world, or a practitioner working in the sector, this course will take you to the next level and prepare you for a career as a transport modelling specialist.
97% of our graduates find employment in a professional or managerial role, or continue with further studies.*
Experience a course designed in collaboration with employers, learning skills the industry desperately needs to unlock the full potential of big data.
Learn to think creatively, beyond the standard application of established solutions, and use your technical expertise across multiple scenarios.
Develop and apply mathematical models to analyse and improve the performance of transportation networks and flows:
And experience what it is like to be part of a project team working across disciplinary boundaries within the transport sector. Through this, gain insights into how modelling, environmental science, planning, economics and engineering can work together to develop sustainable solutions to global challenges. This industry-inspired approach will enable you to apply your knowledge to real-world issues in the field.
Your colleagues will be among the best and brightest from the UK and across the globe. Together you will learn mathematical modelling skills that can be applied to design smarter transport solutions founded on robust methods.
With a strong focus on industry needs, our degrees will prepare you for employment in your chosen field. They will also address the multi-disciplinary nature of transport – enabling you to make effective decisions for clients, employers and society.
Other Study Options
This programme is available part time, allowing you to combine study with other commitments. You can work to fund your studies, or gain a new qualification without giving up an existing job. We aim to be flexible in helping you to put together a part-time course structure that meets your academic goals while recognising the constraints on your study time.
The Complex Systems Modelling - From Biomedical and Natural to Economic and Social Sciences MSc programme will teach you to apply mathematical techniques in the rapidly developing and exciting interdisciplinary field of complex systems and examine how they apply to a variety of areas including biomedicine, nature, economics and social sciences. This research-led course is suitable for graduates who wish to work in research and development in an academic or industrial environment.
The Complex Systems Modelling MSc is an innovative study programme that explores the latest research in the rapidly developing and exciting interdisciplinary field of cpmplex systems.
Modern societies rely on a broad range of infrastructures, institutions and technologies, and their complexities have grown dramatically in the recent past. Consequently, there is a rapidly expanding demand for expertise in complex systems modelling as a foundation for understanding, maintaining and further developing of such systems.
The programme offers you the choice to study either full or part-time. You must take a combination of required and optional modules totalling 180 credits to complete the course. If you are studying full-time, you will complete the course in one year, from September to September. If you are studying part-time, your programme will take two years to complete. You will study the required modules in the first year, and a further selection of required and optional modules including the complex systems modelling module in your second year.
You will study key natural and biomedical scientific topics as well as economic and social sciences. We also offer the opportunity to study an additional zero-credit module called foundations for complex systems modelling and cross-disciplinary approaches to non-equilibrium systems and is designed as a refresher module covering vital mathematics and physics skills.
For graduates in mathematics, or in other suitable scientific disciplines with a strong background in mathematics, who want to work in research and development in an academic or industrial environment. The programme aims to develop a knowledge and understanding of complex systems modelling and their uses, and to enable students to use mathematical techniques to quantify, predict and improve such systems.
Primarily written examinations, some with coursework element, in eight lecture modules, plus an oral presentation and assessed report on the research project.
Our graduates are highly sought after: the applicability of complex systems modelling to areas as diverse as biomedical, natural, economic and social sciences, results in a broad range of opportunities. Some graduates are employed by the companies or laboratories that supervise their MSc research projects, or continue to PhD study.
Other career destinations include:
In this MRes Mathematical Sciences course, you will gain deep knowledge of a chosen topic in mathematics or statistics and develop your research skills in project planning, reviewing literature, group discussions, research presentations and writing publications.
You can choose to work with experts from a range of areas including quantum cryptography, graph theory, statistical analysis, bioinformatics and mathematical modelling.
You will take three taught modules each providing you with the underpinning theory to support your research work.
Visit us on campus throughout the year, find and register for our next open event on http://www.ntu.ac.uk/pgevents.
This programme reflects and benefits from the strong research activities of the Department of Mathematics.
The taught modules and dissertation topics are closely aligned with the interests of the Department’s four research groups:
During the first two semesters you will take a range of taught modules from an extensive list of options, followed by an extended research project conducted over the summer under the supervision of a member of the department, culminating in the writing of a dissertation.
This programme is studied full-time over one academic year. It consists of eight taught modules and a dissertation.
Example module listing
The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
Mathematics is not only central to science, technology and finance-related fields, but the logical insight, analytical skills and intellectual discipline gained from a mathematical education are highly sought after in a broad range of other areas such as law, business and management.
There is also a strong demand for new mathematics teachers to meet the ongoing shortage in schools.
As well as being designed to meet the needs of future employers, our MSc programme also provides a solid foundation from which to pursue further research in mathematics or one of the many areas to which mathematical ideas and techniques are applied.
Knowledge and understanding
Intellectual / cognitive skills
Professional practical skills
Key / transferable skills
We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.
In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.
Non-equilibrium processes underpin many challenging problems across the natural sciences. The mission of the Non-Equilibrium Systems: Theoretical Modelling, Simulation and Data-Driven Analysis MSc is to provide students an insight into cross-disciplinary approaches to non-equilibrium systems, focussing on the three key strands of theoretical modelling, simulation and data-driven analysis. It draws on a broad range of expertise in Mathematics, Physics, Chemistry, Informatics, Computational and Systems Biomedicine, Earth and Environmental Sciences at King’s College London. This course is an ideal study pathway for graduates who wish to work in research and development in an academic or industrial environment.
The Non-Equilibrium Systems: Theoretical Modelling, Simulation and Data-Driven Analysis MSc programme aims to provide you with deeper insights into non-equilibrium processes using theoretical modelling, simulation and data-driven analysis and prepare you for roles within active research.
You will complete the course in one year, studying September to September and taking a combination of required and optional modules totalling 180 credits. The broad range of optional modules will allow you to develop a study pathway that reflect your interests.
We also offer the opportunity to explore an additional zero-credit module called Foundations for CSM and CANES, designed as a refresher module covering vital mathematics and physics skills.
For more information visit http://www.kcl.ac.uk/innovation/groups/noneqsys/Handbook/MSc%20Handbook/CANES-MSc-Programme/CANES-MSc.aspx
For graduates with excellent undergraduate or equivalent qualifications in any relevant discipline (including; mathematics, physics, chemistry, engineering, materials science, biophysics, geophysical sciences and computer science) who want to work in research and development in an academic or industrial environment. The programme aim is to develop deeper insights into non-equilibrium processes using theoretical modelling, simulation and data-driven analysis and prepare students ideally for active research.
We use lectures, seminars and group tutorials to deliver most of the modules on the programme. You will also be expected to undertake a significant amount of independent study.
Each module in your degree is worth a number of credits. You are expected to spend approximately 10 hours of effort for each credit (so for a typical module of 15 credits this means 150 hours of effort). These hours cover every aspect of the module: lectures, tutorials, labs (if any), independent study based on lecture notes, tutorial preparation and extension, coursework preparation and submission, examination revision and preparation, and examination.
Assessment methods will depend on the modules selected. The primary methods of assessment for this course are written examinations and coursework. You may also be assessed by reports, problem sets and oral presentations.
Leads to PhD study or careers in teaching, industrial research or the financial sector.