Location: | Sheffield |
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Salary: | £37,099 to £45,585 per annum (Grade 7) |
Hours: | Full Time |
Contract Type: | Fixed-Term/Contract |
Placed On: | 25th July 2024 |
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Closes: | 22nd August 2024 |
Job Ref: | UOS041644 |
Contract type: Fixed-term for three years from October 2024
The Dynamics Research Group at the University of Sheffield is seeking to appoint a highly-motivated Research Associate in Dynamics to carry out a research project on “new machine learning methods for populations of cardiac digital twins”.
This post offers an exciting opportunity to work within a leading UK dynamics research group as part of a research project to create new technologies for population-based modelling of cardiac digital twins (EPSRC Programme Grant - Networks of Cardiovascular Digital Twins (CVD-Net)). The project is a consortium between Imperial College London, the Universities of Sheffield and Nottingham and several industrial partners. See pbshm.ac.uk.
The Research Associate will take a leading role in the development and delivery of their research relating to machine-learning approaches for populations of cardiac digital twins. In particular, they will develop methods for Bayesian and geometric physics-based models, particularly electrochemical and finite-element models, with a focus on the heart; they will also conduct uncertainty analysis based on the heart models. There will be multiple opportunities to collaborate with research teams and industrial partners within the ROSEHIPS consortium. This will range from basic research activities right through to aspects of commercialisation and exploitation of research results where applicable.
The successful candidate will have excellent research and coding skills in engineering dynamics or a closely related discipline. You will also have excellent communication skills and proven experience in writing high quality scientific papers and giving research presentations to both an academic and industrial audience. You will be able to develop new research ideas, and work collaboratively with team members and other consortium partners.
The CVD-Net Network provides a UK wide network of excellence employing a team of Research Associates (including this post) and several linked PhD students. Research activities will be complemented by network-wide events including a comprehensive programme of scientific meetings and a smaller number of training events. In addition, consortium members are encouraged to disseminate their research results at leading international conferences, all of which will provide excellent career development opportunities.
Applicants should have, or be about to obtain, a PhD in computer science, engineering, mathematics or a relevant discipline.
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