英国埃克塞特大学博士后职位---基于数值建模的医疗保健决策

英国埃克塞特大学博士后职位---基于数值建模的医疗保健决策

Postdoctoral Research Fellow

University of Exeter

Description

The College wishes to recruit a Postdoctoral Research Fellow to participate in a project looking at the use of statistical methods for uncertainty quantification for improved decision making in healthcare based on numerical models. This EPSRC funded post is available from 1 January 2023 or as soon as possible after that for 1 year. The successful applicant will develop new methods for uncertainty quantification (particularly for the calibration of imperfect models with uncertainty real world data), they will also carry out a number of case studies working with clinicians and numerical models to improve decision making and hopefully clinical outcomes.

The post will include the development of new statistical methodology, building on the work currently being carried out at the University of Exeter, and the application of this, and existing methodology for uncertainty quantification, to real world clinical use of numerical models.

About you

The successful applicant will be able to develop research objectives, projects, and proposals; identify sources of research funding and contribute to the process of securing funds and make presentations at conferences and other events.

Applicants will possess a relevant PhD or equivalent qualification/experience in a related field of study. The successful applicant will be an expert in statistics or mathematical modelling and possess sufficient specialist knowledge in the discipline to develop research programmes and methodologies. The successful applicant will also be able to work collaboratively, supervise the work of others and act as team leader as required. Applicants will be able to work effectively with a range of people including clinicians and numerical modellers. They will have a knowledge of (or will be able to quickly gain one) of modern statistics, machine learning, artificial intelligence, and mathematical modelling.

Exceptional communication skills are critical, as the successful candidate 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. Additionally, the successful candidate will have a demonstrable ability to write up scientific findings in a timely and succinct way for publication.