Ref. 50069206
Salary £45,791 to £50,855 per annum (Incl. LWA)
Department/School Liberal Arts and Sciences, School of Life Sciences
Location 115 New Cavendish Street, Central London
This post is full time, 35 hours per week and is fixed term until 01 March 2026.
We are looking to recruit a PDRA to join the Research Centre for Optimal Health in the School of Life Sciences at the University of Westminster to work on a research project funded by Diabetes UK.
You will join a research project in collaboration with the University of Lincoln that encompasses understanding the genetic basis of adiposity subtypes and their implication for Type 2 Diabetes. This specific role will focus on the development and application of novel image-processing techniques to large collections of clinical MRI data and the use of those derived measures for the modelling of health, disease, and ageing.
As a key member of a multidisciplinary team, you will develop new imaging phenotypes and biomarkers with particular relevance to Type 2 Diabetes and use these in combination with non-imaging data, including lifestyle, metabolomics and primary care data, to answer scientific questions of interest. You will manage your own academic research, coordinate both internally and externally with collaborators and produce manuscripts for submission to leading scientific journals.
The successful candidate must be highly motivated and have an advanced degree (Ph.D.) in computer science, electrical or biomedical engineering, physics, statistics, or related fields. Previous experience in software development practices (version control, unit testing, CI/CD), cloud-based computing environments, and GPU-based computing is preferred.
Experience programming in Python is preferred. Knowledge of other languages, such as MATLAB, R or Julia, is a plus. Previous experience with machine learning or neural networks applied to large, unstructured collections of data is a plus. Previous experience with research focusing on biomedical image and signal processing, medical image computing or magnetic resonance imaging is advantageous.
Our research team follows a hybrid work structure where employees can work remotely or from the office, as needed, based on specific tasks or personal preferences.
To apply for this vacancy please click above. Further information can be found in the job description and person specification, which can be accessed through link below.
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We are fully committed to enabling a supportive and safe learning and working environment which is equitable, diverse and inclusive, is based on mutual respect and trust, and in which harassment and discrimination are neither tolerated nor acceptable.
The University has adopted Smart Working principles to support and further our Equality, Diversity and Inclusion aims of being an inclusive, collaborative and flexible employer. Further details of Smart Working can be discussed at interview stage.
Closing date: midnight on 17 June 2024
Interviews are likely to be held on: 01 July 2024
Administrative contact (for queries only):[email protected]
JOB DESCRIPTION AND PERSON SPECIFICATION