Research Fellow in Machine Learning and Quantitative Imaging Biomarker

University of Westminster
April 08, 2024
Offerd Salary:£45,791 - £50,855
Working address:N/A
Contract Type:Other
Working Time:Full time
Working type:N/A
Ref info:N/A
Research Fellow in Machine Learning and Quantitative Imaging Biomarkers

Ref. 50068848

Salary £45,791 - £50,855 per annum (Incl. LWA)

Department/School School of Life Sciences

Location New Cavendish Street, London

This post is full time, 35 hours per week and is fixed term until 31 May 2025.

We are seeking a talented researcher to join our team at the Research Centre for Optimal Health. As part of our ongoing research project, you will focus on developing and applying cutting-edge image processing techniques to extensive collections of medical images, resulting in the creation of novel biomarkers. Your work will drive analyses to explore age-related and health-related outcomes using quantitative biomarkers derived from imaging and healthcare datasets. In this role, you will contribute to our research and development efforts, and take a lead role in writing scientific papers. Join us in advancing healthcare through innovative research!

As part of our exciting research project, you will focus on biomedical data analysis, medical image computing, and machine learning. While previous experience in these areas is advantageous, it is not essential. Familiarity with magnetic resonance imaging (MRI) is preferred. The ideal candidate will hold a PhD in a relevant field (e.g., Computer Science, Bioengineering, Biology, Data Science, Statistics) and possess strong coding skills in R or Python. Proficiency in handling large datasets and understanding programming processes and best practices for data analysis is essential. Experience with biomedical image processing, machine learning, high-performance computing environments, statistical analysis, and data science techniques is desirable. Knowledge of human physiology and anatomy is a plus. Familiarity with Linux systems and Git/GitHub is also beneficial.

The candidate will be expected to communicate the results derived from data analysis, leading and contributing to research reports and papers intended for publication in scientific journals and have a strong willingness to learn and adapt to new challenges.

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.

At the University of Westminster, diversity, inclusion and equality of opportunity are at the core of how we engage with students, colleagues, applicants, visitors and all our stakeholders.

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 08 April 2024

Interviews are likely to be held on: 15 April 2024

Administrative contact (for queries only):[email protected]


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