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Senior Research Associate (Machine Learning in Medical Image Analysis)


Grade 8: £42,149 - £50,296 per annum

Closing date

Nov 26, 2021 12:00PM


We are seeking a full-time Senior Research Associate to join the Oxford Biomedical Image Analysis Laboratory in a pivotal role, as part of the Oxford component of an international collaboration with the Hong Kong based Centre for Cerebro-cardiovascular Health Engineering (COCHE).  This is a rare opportunity to join an internationally leading inter-disciplinary team conducting research on novel computational methods for analysis of biomedical images and  early-stage clinical translation in collaboration with clinical partners. The post is available for three years in the first instance. You will be leading, devising, coordinating and supervising research projects in fetal and maternal cardiovascular image analysis, including work involved in the collaborations with project partners, guidance to researchers and students, and securing further funding to underpin the research.


COCHE has been established to develop new ways to treat cardiovascular disease (CVD) with innovative technologies allowing early prediction and intervention, so people can stay a step ahead of the disease. The developed technologies aim to reduce the human cost, as well as alleviate both the financial and social burden on healthcare systems worldwide. The Oxford-based imaging project associated with COCHE concerns the development of the underpinnings of a simple-to-use low-cost ultrasound device for checking the health of the fetal heart.


You should have a relevant PhD with a defined breadth and depth of relevant post-qualification research experience, as well as a strong publication record.  You should also have experience of both original video image analysis algorithm development and validation of AI models on real-world data.  Good written and oral communication skills are essential, as well as the ability to prioritise a busy workload and lead a small team. Excellent programming skills and experience with deep learning toolkits is also essential.


Informal enquiries can be directed to Professor Alison Noble 


Only online applications received before midday on Friday, 26 November 2021 can be considered. You will be required to upload a covering letter/supporting statement, including a brief statement of research interests, CV and the details of two referees as part of your online application.


The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology.

Contact name

Professor Alison Noble

Contact email