MSc by Research in Mathematics of Complex Systems

Key information & fees

Duration of programme: One year full-time (three months of taught modules and a nine month individual project), or two years part-time

Start date: October

Intake: Approximately 10 per year for UK/EU students (expected to increase chronologically) and 15 per year for international students

Application details:
Apply for this course online

Contact us:

Research Student Coordinator

T: +44 (0)121 204 3663

    +44 (0)121 204 3500

F: +44 (0)121 204 3685

E: seasres@aston.ac.uk

Academic Information:

Programme Director: Dr Amit K Chattopadhyay (a.k.chattopadhyay@aston.ac.uk)

Information on visas for international students

Entry requirements

 Applicants must achieve a minimum of a 2:2 Honours Degree in a numerate science from a UK University, or an equivalent international qualification. The Programme Director may conduct an interview in person or by telephone. International students whose native language is not English will also need to demonstrate English Language ability as per university requirements.

Programme outline and modules

This programme is designed to train aspiring scientists and budding IT professionals who wish to rely on numerical proficiency to further their career goals. The programme consists of a training aspect of taught components (4 modules, first 3 months) and a significant interdisciplinary research project in complex systems (9 months). Research topics are chosen by students from a list of topics ranging from biology to finance and are supervised by academics from the Non-linearity and Complexity Research Group (NCRG) at Aston.

Modules

This MSc integrates a taught component of four modules over three months (50 credits) with a substantial individual research project lasting nine months (130 credits).

• Algorithms and Computational Mathematics (10 credits): Linear algebra, optimisation and numerical analysis

• Introduction to Methods of Statistical Physics (10 credits): Statistical physics and many body theory

• Statistical Pattern Analysis and Probabilistic Modelling (15 credits): Probabilistic models, Bayesian inference, decision theory & Monte Carlo methods
• Stochastic and Non-Linear Dynamical Systems (15 credits): Dynamics of deterministic and random systems using ODEs, applications in biology & finance

• Research Project (130 credits): Research work in the general field of complexity to be jointly chosen by the supervisor and student.

Career prospects

The programme has been designed to meet the huge demand for mathematically skilled experts both in the academic and industrial arena. Graduates may be employed in a broad range of positions: research and development teams as a part of a large company, in start-ups, or as consultants. We expect a substantial fraction of graduates from this programme to join research teams in high-tech engineering and IT sectors. Previous evidence suggests that such employment prospects are good. Projects in collaboration with an industrial partner have traditionally provided excellent opportunity to forge links with industry that may result in subsequent employment.

Programme Director

Dr Amit K Chattopadhyay

After obtaining a Ph.D. in theoretical physics (2001), Dr Chattopadhyay took up high profile research positions in Germany, UK, Italy and India. He has authored and co-authored over 30 publications in international peer reviewed journals and has been awarded the Alexander von Humboldt fellowship and the Marie Curie Incoming International Fellowship, the two highest research awards in Europe for his researches in mathematical biology and statistical physics. He is a  co-author of a leading textbook in `Heat and Thermodynamics’ with the same title. Details of his research profile are available here.