EPSRC Centre for Doctoral Training in Industrially Focused Mathematical Modelling

Lead Research Organisation: University of Oxford
Department Name: Mathematical Institute


This Centre for Doctoral training in Industrially Focused Mathematical Modelling will train the next generation of applied mathematicians to fill critical roles in industry and academia. Complex industrial problems can often be addressed, understood, and mitigated by applying modern quantitative methods. To effectively and efficiently apply these techniques requires talented mathematicians with well-practised problem-solving skills. They need to have a very strong grasp of the mathematical approaches that might need to be brought to bear, have a breadth of understanding of how to convert complex practical problems into relevant abstract mathematical forms, have knowledge and skills to solve the resulting mathematical problems efficiently and accurately, and have a wide experience of how to communicate and interact in a multidisciplinary environment.

This CDT has been designed by academics in close collaboration with industrialists from many different sectors. Our 35 current CDT industrial partners cover the sectors of: consumer products (Sharp), defence (Selex, Thales), communications (BT, Vodafone), energy (Amec, BP, Camlin, Culham, DuPont, GE Energy, Infineum, Schlumberger x2, VerdErg), filtration (Pall Corp), finance (HSBC, Lloyds TSB), food and beverage (Nestle, Mondelez), healthcare (e-therapeutics, Lein Applied Diagnostics, Oxford Instruments, Siemens, Solitonik), manufacturing (Elkem, Saint Gobain), retail (dunnhumby), and software (Amazon, cd-adapco, IBM, NAG, NVIDIA), along with two consultancy companies (PA Consulting, Tessella) and we are in active discussion with other companies to grow our partner base. Our partners have five key roles: (i) they help guide and steer the centre by participating in an Industrial Engagement Committee, (ii) they deliver a substantial elements of the training and provide a broad exposure for the cohorts, (iii) they provide current challenges for our students to tackle for their doctoral research, iv) they give a very wide experience and perspective of possible applications and sectors thereby making the students highly flexible and extremely attractive to employers, and v) they provide significant funding for the CDT activities.

Each cohort will learn how to apply appropriate mathematical techniques to a wide range of industrial problems in a highly interactive environment. In year one, the students will be trained in mathematical skills spanning continuum and discrete modelling, and scientific computing, closely integrated with practical applications and problem solving. The experience of addressing industrial problems and understanding their context will be further enhanced by periods where our partners will deliver a broad range of relevant material. Students will undertake two industrially focused mini-projects, one from an academic perspective and the other immersed in a partner organisation. Each student will then embark on their doctoral research project which will allow them to hone their skills and techniques while tackling a practical industrial challenge.

The resulting doctoral students will be highly sought after; by industry for their flexible and quantitative abilities that will help them gain a competitive edge, and by universities to allow cutting-edge mathematical research to be motivated by practical problems and be readily exploitable.

Planned Impact

The CDT in Industrially Focused Mathematical Modelling has been designed by academics and industrialists to enable modern quantitative methods to be readily and efficiently applied to industrial problems, thereby creating rapid impact through competitive advantage. The training includes aspects that will allow students to appreciate the business context within which the application of their mathematical research sits and hence understand where such application might have greatest influence. The emphasis on team working and interaction with different disciplines will create an environment where the insight gained from the mathematical ideas can be fully exploited. The cohort-based training of the CDT is directly aimed at ensuring that the students have continual active interactions and discussions so that identifying opportunities for technology transfer between the many industrial projects that they engage in will be a natural activity. The impact will be realised both through direct exploitation of the mathematical ideas by our partner companies and through more general dissemination routes to a wider industry base, for example through our annual meeting and appropriate forms of publication. The mini-projects enable new partners to engage at a relatively easily level, where they can assess possible impact, before progressing through to the longer research project element.

Our industrial partners have given some indication of the level of impact that they expect from the interaction with the CDT. In particular several letters highlight the extensive track records they have in funding Oxford internships and DPhils associated with supervisors who will be in the CDT. Furthermore, our students will graduate with the skills needed to operate successfully in industry and, as several companies indicate in their letters of support, will be ideal employees.

We have specifically engaged two partners, the Smith Institute in the UK and Teknova in Norway who have a major role in facilitating mathematical interaction between industry and academia. We are therefore ideally placed to ensure that the widest possible set of companies are aware of the CDT and its benefits. These partners will also be in a position to identify where the outputs of the CDT might be exploited through technology transfer opportunities.

We will have annual events where the cohorts will present their ideas and where we draw in a larger industrial audience in order both to widen our connections and possible partners but also to disseminate the ideas into the industrial community where possible exploitation might be identified.



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