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Details of Grant 

EPSRC Reference: EP/L015684/1
Title: EPSRC Centre for Doctoral Training in Statistical Applied Mathematics at Bath (SAMBa)
Principal Investigator: Cox, Professor AMG
Other Investigators:
Douglas, Dr S Wood, Professor SL
Researcher Co-Investigators:
Project Partners:
AMEC Amgen Ltd AstraZeneca
Cytel Det Norske Veritas BV DNV EDF
GKN Home Office King Abdullah University of Sci and Tech
Olsen Ltd Quintessa Ltd Schlumberger
Takeda Europe Research & Development Cen
Department: Mathematical Sciences
Organisation: University of Bath
Scheme: Centre for Doctoral Training
Starts: 01 May 2014 Ends: 31 October 2023 Value (£): 4,006,757
EPSRC Research Topic Classifications:
Algebra & Geometry Non-linear Systems Mathematics
Numerical Analysis Statistics & Appl. Probability
EPSRC Industrial Sector Classifications:
Financial Services Pharmaceuticals and Biotechnology
Energy Information Technologies
Related Grants:
Panel History:
Panel DatePanel NameOutcome
23 Oct 2013 EPSRC CDT 2013 Interviews Panel D Announced
Summary on Grant Application Form
Together with industrial partners, we have established that there is a strong unmet demand for individuals with expertise in the combination of statistics, applied mathematics, computation, and the collaborative problem solving skills required to acquire application area knowledge. Consider, for example, aircraft structural design, where statistical methods have recently been approved in the certification of aircraft, complementing traditional experimental testing. This ushers in a change in possible design methodology, but creates a corresponding gap for the necessary talent in the workforce: scientists with knowledge of materials, computational methods and statistics. Such individuals are needed to sustain the UK's global competitive advantage, industrially and academically. We propose a world leading and innovative cohort-driven centre for doctoral training at the interface of Statistics and Applied Mathematics: Statistical Applied Mathematics at Bath (SAMBa).

Modern mathematical models describing real world applications must incorporate randomness and data in a variety of ways in order to improve their ability to predict complex behaviour and describe empirical observations. Traditionally, deterministic applied mathematics and statistical methods have taken different approaches in modelling observed phenomena. More recently, we have seen that this is proving to be a hindrance to the competitiveness of British mathematics, especially when taking account of the enormous scope for research with genuine real-world impact.

SAMBa will create a new generation of interdisciplinary mathematicians, both for academic careers as well as for insertion into British industry. Their primary strengths will be their problem solving ability and their fearlessness of barriers separating mathematical modelling and modern statistics. Moreover, the implementation of this CDT will promote a novel way of educating UK PhD students within the mathematical sciences, in which there is horizontal cross-disciplinary and industrial integration through CDT activities.

The central mechanism by which this horizontal integration will occur will be through week-long Integrative Think Tanks (ITT), which share similarities with sandpits. These ITTs will be supported by an array of new courses that span a spectrum including statistics, stochastic simulation and applied mathematics.

SAMBa will enrol ten students per year on a four-year study programme. The first year will focus on the new courses and in the formation of research themes, as well as developing cohort integration. ITTs will occur at the end of the first and second semesters during the first year of study, and will give students the opportunity to learn how to formulate problems and structure their approach to problem solving. ITTs will be intensive activities, managed by academic staff together with interdisciplinary and industrial leaders. Students in later years will participate in one ITT per year with a view to enhancing the PhD cohort experience. The expected outcomes of the ITTs will be: to provide real experiences in approaches to problem solving, to promote cross-fertilisation of ideas and expertise through horizontal integration, to build a cohesive PhD student cohort, to catalyse new collaborations, and to provide a source of PhD thesis projects. It is expected that most, but not all, PhD thesis problems and supervisory teams will emerge from ITTs. PhD students will also run a symposium series to prepare for, and subsequently reinforce, the ITT experience as well as to develop the students' sense of research empowerment.

Students in SAMBa will be awarded an M.Res. after one year, subject to successful assessment. In addition, we will strongly encourage three month industrial or cross-disciplinary academic placements. These placements will enhance the horizontal integration and are a natural extension of our long-standing and thriving BSc an MSc placement scheme.
Key Findings
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Potential use in non-academic contexts
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Organisation Website: http://www.bath.ac.uk