About this role
About the role
We are seeking a Research Assistant/Associate to join the Biomedical Image Analysis (BioMedIA) Group at Imperial College London to work on the EPSRC CVD-Net Programme Grant. The programme aims to develop digital twin models of the heart for patients with pulmonary arterial hypertension. This post links medical imaging research with digital twin models.
What you would be doing
You will undertake research in cardiac image analysis, machine learning and predictive modelling to derive imaging phenotypes and anatomical models from cardiac images, which form important aspects of the digital twin model that can predict future outcomes of the patients. Research outcomes will be expected to be published in high-quality refereed international conferences and/or journals. The successful candidate will be expected to have an outstanding background in medical image analysis, machine learning and programming.
What we are looking for
Hold a PhD (or near completion) in medical image analysis, image processing, computer vision or a closely related discipline, or equivalent research experience. Proven experience and publication track record in medical image analysis, image processing, computer vision and machine learning. Excellent programming skills. Excellent verbal and written communication skills and the ability to write clearly and succinctly for publication. Motivation of improving healthcare via computational and machine learning techniques.
What we can offer you
An excellent opportunity to continue your career at a world-leading institution (2nd place in the QS World University Ranking) and be part of our mission to continue science for humanity. Learning and collaboration opportunities within an inclusive, collegial, world-leading research environment. Our group deliver excellent research outcomes in AI conferences and medical imaging journals. Gain access to Imperial’s sector-leading dedicated career support for researchers as well as opportunities for promotion and progression. Sector-leading salary and remuneration package. Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing.
Further information
This is a full-time post with a fixed-term contract for 36 months.
In addition to completing the online application candidates should attach:
A full CV with list of publications A 1-page research statement on how your experience meets the above requirements.
If you require any further details about the role, please contact: Dr Wenjia Bai – [email protected], with [RA Post] in the subject of the email and your CV.