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Postdoctoral Research Fellow

University of Exeter - College of Engineering, Mathematics and Physical Sciences

Location: Exeter
Salary: £34,520 to £38,833 on Grade F, dependent on knowledge, skills and experience.
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 20th July 2018
Closes: 20th August 2018
Job Ref: P63408

Two Research Fellows are required to support the EPSRC Centre for Predictive Modelling in Healthcare (CPMH). The roles are available from 01 October 2018, or a mutually agreeable date soon thereafter, for a period of up to 24 months.

The CPMH is a GBP 2M award which brings together outstanding scientists from mathematics, statistics, computer science and our medical school. With an additional GBP 7M in research funding, the interface between mathematics, computer science and healthcare is one of the most rapidly expanding areas within the University. The Centre forms part of the Quantitative Biology and Medicine Initiative, which currently consists of 15 PDRAs, 9 fellowship holders, and 10 PhD students.

The successful candidates are expected to focus on one of the following areas, depending on their interests and background:

  • (a) Transient dynamics of networks with multiple time scales: there are significant mathematical challenges from disease modelling that require the development of new techniques to understand transient behaviour in multiple timescale systems, especially for systems where there is not a simple factorization into fast and slow subsystems.
  • (b) Numerical investigation of models of cardiac diseases: involving multi-scale excitable and transient dynamics, with a focus on re-entrant arrhythmias specifically concerning development and improvements of antiarrhythmia pacing, low-voltage defibrillation and catheter ablation. [In partnership with cardiologists at the RD&E Hospital, Exeter].
  • (c) Mathematical modelling and analysis of EEG in dementia: EEG analysis has shown promise in differentiating people with dementia from healthy older adults, and therefore could provide indications for early diagnosis. We will use mathematical models to better understand why differences in EEG occur and combine models and analysis to build improved diagnostic markers. [In partnership with colleagues in Bath, Bristol & Reading].
  • (d) Mathematical modelling and analysis of polygenic disease: conditions such as diabetes and dementia depend on the simultaneous presence of several genes; they are not inherited as simply as single-gene diseases and therefore require the development of new mathematical approaches to improve diagnosis via e.g. the interpretation and uncertainty quantification of proportions of patients in large data sets (e.g. UK Biobank) using genetic risk scores. [In partnership with diabetologists and neurologists from the medical school].

Exceptional communication skills are critical as the post-holders will work in an interdisciplinary team and will need to present information on research progress and outcomes, as well as having the ability to communicate both verbally and in writing complex information to scientists and stakeholders without a mathematics background.

To view the Job Description and Person Specification document please click here.

For further information please contact Centre Director Professor John Terry, e-mail or telephone (01392) 725274.

The College is working towards department Silver Athena SWAN awards as a commitment to providing equality of opportunity and advancing the representation of women in STEM/M subjects: science, technology, engineering, mathematics and medicine. 


Candidates should upload a CV, a cover letter describing how they satisfy the essential criteria for the role and a recent publication that showcases their research. This should be submitted as a single PDF attachment.

The University of Exeter is an equal opportunity employer.  We are officially recognised as a Disability Confident employer and an Athena Swan accredited institution.  Whilst all applicants will be judged on merit alone, we particularly welcome applications from groups currently underrepresented in the workforce

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