A Multi-disciplinary Approach to a Novel Biological Problem – data analysis and modelling

Data analysis and modelling of data for a multi-disciplinary grant application to support an innovative approach to a current biological problem as part of a Royal Society funded project to change our approach to research.

Department: Biomedical Sciences

Supervised by: Shirley J Keeton

The Placement Project

The Royal Society, an independent scientific academy dedicated to promoting excellence in science has awarded Dr Shirley Keeton (School of Biological Sciences) funding to revolutionise how multi-disciplinary research is developed and driven by early career researchers. In recent years a multi-disciplinary approach to solving a biological problems has provided the opportunity to explore some interesting approaches, exploiting new and emerging technologies in innovative ways. A recent Royal Society initiative has focused on creating and promoting the best conditions for UK research to flourish in a global setting and as part of this initiative a small grant was awarded to pilot an innovative approach to running an early career scientist lead multidisciplinary project at University of Reading. The multi-disciplinary project team will comprise 4 early career scientists from Biology and three other disciplines (for example, maths, business, pharmacy, food science, chemistry) and will tackle a biological problem with a view to producing a grant proposal. An undergraduate student will be offered the opportunity to join the team to help analyse and model data to support the grant application. This UROP project will involve data analysis and modelling and the student work closely with members of the project team to generate the grant data and the grant proposal. This is an exciting opportunity to be part of a new and innovative approach to conducting a research project the outcome of which will feed forward into changes in research culture across universities countrywide. We aim to select two students with different backgrounds and a willingness to engage and use their skills to assist in the completion of the grant proposal.


The specific tasks to be undertaken will be defined by the project group. It is envisaged that one studentship will involve laboratory work and the other will involve data modelling. The students will be able to develop their communication skills by presenting at regular laboratory meetings. The specifics of the project will be defined by the project group early in 2019 and discussed and developed with the UROP student before the studentship commences.

Skills, knowledge and experience required

Students from all life sciences, pharmacy, food science, mathematics and Henley business school are invited to apply. Students should have a keen interest in a multi-disciplinary approaches to problem solving, should be self-motivated, strong communicators and comfortable working in a team environment.

Skills which will be developed during the placement

The students will gain invaluable experience working with early career scientists in a team environment to write a research proposal/grant for a multi-disciplinary project. They will gain an understanding of how to run a short pilot project to generate grant proposal data and how to present that data in a suitable format. Through the project the student will gain important transferrable skills invaluable in conducting good research: planning, time management, trouble shooting and problem solving as well as communication skills appropriate to this level of project. They will also have the opportunity to discuss and present data in an academic environment.

Place of Work

Whiteknights campus, University of Reading

Hours of Work

37 (may be flexible)

Approximate Start and End Dates (not fixed)

Monday 01 July 2019 - Monday 30 September 2019

How to Apply

The post will be advertised centrally on the UROP website between 25th February and 5th April 2019. Interested students should send a CV and covering letter to Dr Shirley Keeton: Successful candidates will then be invited to interview.

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