Research Associate - Large-Scale Cardiac Image Analytics

Applications are invited for a Research Associate position, funded by the British Heart Foundation Manchester Research Excellence Award, within the Division of Informatics, Imaging & Data Sciences at the University of Manchester. The successful candidate will join the Centre for Computational Imaging and Modelling in Medicine (CIMIM), a dynamic team of researchers advancing the frontiers of AI and medical imaging.

Overall Purpose of the Job

We are seeking to appoint a researcher with experience in medical imaging and machine learning. The post, under the supervision of Dr Jinming Duan, is available as soon as possible, and will focus on large-scale cardiac image analytics. Applicants should hold, or be about to obtain, a PhD (or equivalent) in physics, engineering, computer science or applied mathematics. The successful candidate is expected to have experience in artificial intelligence and machine learning, big data processing, cardiac image analysis, data visualisation and statistical methods. Strong organisational skills, self-motivation, and excellent communication abilities are essential. A strong record of publication in internationally peer-reviewed journals is highly desirable.

The purpose of this role is to develop and apply advanced machine learning techniques to automate and accelerate the analysis of large-scale cardiac imaging datasets. The work will involve building deep learning pipelines for image segmentation, motion analysis, and data integration to support the diagnosis and prognosis of cardiovascular disease.

The appointed PDRA will:

• Design and implement end-to-end, trainable deep neural networks for whole-heart segmentation, co-registration, and shape reconstruction;
• Utilise high-performance computing platforms to perform inference and quantitative phenotyping across the UK Biobank cardiac MRI dataset;
• Explore novel temporal parameterisation methods for cardiac motion using feature tracking and Transformer-based architectures;
• Apply these advanced methods to enable accurate assessment of biventricular structure and function, with the goal of identifying heart disease and informing patient prognosis.

Along with your application, you should submit a single file containing your CV, list of publications, and research statement (max 2 pages). We support applications from those returning from a career break and are happy to discuss flexible working arrangements.

What you will get in return:

• Fantastic market leading Pension scheme
• Excellent employee health and wellbeing services including an Employee Assistance Programme
• Exceptional starting annual leave entitlement, plus bank holidays
• Additional paid closure over the Christmas period
• Local and national discounts at a range of major retailers

As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit. Our University is positive about flexible working.

Hybrid working arrangements may be considered.

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies. Any recruitment enquiries from recruitment agencies should be directed to People.Recruitment@manchester.ac.uk. Any CVs submitted by a recruitment agency will be considered a gift.

Enquiries about the vacancy, shortlisting and interviews: General enquiries: Email: People.recruitment@manchester.ac.uk Technical support: jobseekersupport.jobtrain.co.uk/support/home This vacancy will close for applications at midnight on the closing date.