Mathematics Innovation Research Associate

The University of Surrey is a global community of ideas and people, dedicated to life-changing education and research.

We are ambitious and have a bold vision of what we want to achieve - shaping ourselves into one of the best universities in the world, which we are achieving through the talents and endeavour of every employee.

Our culture empowers people to achieve this aim and to collectively, and individually, make a real difference.

The role

We are seeking two talented and versatile mathematicians to join the School of Mathematics and Physics at the University of Surrey to lead the formation of a new team of interdisciplinary mathematical researchers. This role is partially funded by the Mathematical Innovators in the Digital Space Flexible Fund scheme.

As part of the role, you will be expected to work within interdisciplinary academic teams to:

• Work across different long-term and occasional short-term projects with diverse partnerships;
• Interface between academics in the Mathematics at the Interface and Fundamental Mathematics research groups and other partners in academia and industry;
• Learn about and implement new modelling techniques for interdisciplinary projects;
• Culture your own mathematical identity with a broad base of expertise;
• Demonstrate therewith leadership through the development of novel data-centric mathematical modelling within other disciplines;
• Engage in collaborative grant capture and impact acceleration.

About You

The successful candidate will have a PhD (or equivalent) in Mathematics or a closely related discipline, and ideally with experience of collaborative interdisciplinary working. You will also have some experience in presenting your work to a wide range of stakeholders and a track record of publishing novel scientific research. We are particularly interested in candidates who can evidence their experience with as many of the following areas as possible, preferably at least two:

• Interdisciplinary mathematical modelling
• Machine learning and/or other quantitative modelling in AI
• Statistical modelling
• Numerical analysis and scientific computing.

The posts are full-time and are fixed term for a period of up to 24 months.

How To Apply

To apply please upload your CV and a cover letter via the university website. In your cover letter, please clearly explain why your skills and experience make you suitable for this role.

Informal enquiries are invited and should be directed to Dr Matt Turner ([email protected]).