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Department of Mathematical Sciences

 Department of Mathematical Sciences

Welcome to the Department of Mathematical Sciences

Mathematical Sciences at Durham offers a unique blend of high quality teaching and research in pure mathematics, theoretical physics, numerical analysis, biomathematics, statistics and probability theory. We pride ourselves on combining world-leading research with commitment to the learning experience of our undergraduate and postgraduate students. Our core objective is to achieve and maintain academic excellence in an environment recognising diversity and a healthy gender balance as undeniable strengths, and to lead by example in our efforts to inspire our young mathematicians, students and researchers, to embrace a career that will continue to provide what attracted them to a Maths degree: the fun of mathematics, its sheer elegance and understated beauty, and the thrill of solving puzzles.

The curriculum and degree structure is frequently revisited and modernized to provide our students with the best possible mathematical and general skills, so that they adapt swiftly in a rapidly changing professional environment. For example we now have a new degree programme with a year in industry that will give interested students practical experience of problem solving in a commercial environment as well as enhance their employability. Read more...

Professor Anne Taormina
Head of Department



Today's Seminars

ECS-Mathematical Sciences Energy Seminars: Measurement-based identification of power system dynamic model & Numerical Methods for Optimal Control

Presented by Janusz Bialek and Max Jensen, Durham University

16 May 2012 14:00 in E240

Janusz Bialek - Measurement-based identification of power system dynamic model (or inverse-engineering approach to eigenanalysis).


Eigenanalysis is a standard tool to analyse power system dynamics whereby the response of a high-order dynamic system is represented as superposition of responses of first- and second-order systems (so-called modes) defined by eigenvalues of the system state matrix. Obviously to determine eigenvalues it is necessary to know the full system model (i.e. the state matrix). This talk will describe an attempt at inverse-engineering eigenanalysis when the unknown system model is extracted from measurements of system modes and mode shapes. Professional help from linear algebra mathematicians is required to explain unexpected results when it was possible to extract the system model from an incomplete set of measurements.

Max Jensen - Numerical Methods for Optimal Control


I begin this short talk reviewing classical results from optimal control theory to place the approach by Bellman into a wider context. I then describe why the numerical solution of the Bellman equation remains a challenging problem. I conclude with some examples to show how this approach has been used to problems in energy production and finance.

Contact or for more information

Mathematical modelling underlies much of energy engineering. At Durham, relevant engineering research ranges from power network reliability, economics and planning, through reliability analysis of generation units, to computational fluid dynamics models of wind and steam turbines. For this reason, ECS and Mathematical Sciences are organising a joint seminar series to explore opportunities for future collaborative research and grant proposals.

Each seminar will consist of a 20-30 minute talk from each discipline, followed by an extended discussion. While these seminars are open to any Durham researcher, the series is tightly focused on discovering topics for future external proposals between the Mathematical Sciences and ECS.

A selection of recent grants

Recent Publications

Contact Details

Dept of Mathematical Sciences
Durham University
Science Laboratories
South Rd.
Durham DH1 3LE

REF2014 RESULTS The 150 years of the LMS CPT BSI