Research Associate in Deep Learning for Medical Imaging job with KINGS COLLEGE LONDON

Job description

This postdoctoral position is funded by a 3-year project grant between King´s College London and Aarhus University, as part of a multicenter study. The candidate will work in an interdisciplinary team consisting of physicists, engineers, computer scientists, biologists, chemists, and clinicians to develop novel deep learning super resolution and image reconstruction techniques to enable free-breathing motion corrected 3D MR coronary artery angiography (CMRA) in a scan time of less than 1 minute or even in a single breathhold. The research will be performed in close collaboration with industry (Siemens Healthineers) and clinicians to allow fast prototyping and validation in a multicenter study. The research team is located in St Thomas´ Hospital in the Department of Biomedical Engineering which has access to 10 state-of-the-art clinical research scanners with field strengths varying from 0.55T, 1.5T, 3T to 7T. The specific objectives of the project will be

1) To devise a super-resolution deep learning network to enable free-breathing motion corrected 3D coronary MR angiography (CMRA) in less than 1 minute.

2) To devise an end-to-end deep learning network to enable joint motion estimation and motion corrected undersampled image reconstruction for 3D CMRA.

The successful applicant will be closely supervised by Prof René Botnar and Prof. Claudia Prieto at the School of Biomedical Engineering and Imaging Sciences and will be part of a vibrant research team of 20 PhD students and postdocs.

Located in the heart of London, King’s is the hub of a global network of strong academic connections and collaboration, with prestigious international partnerships within and across disciplines – scientific and medical, social and creative. King’s is investing in the highest caliber of talent to drive the university forward to achieve its greatest potential. The very best from the United Kingdom and across the globe are invited to join King’s. We are looking for a strong commitment to teaching and research, to push the boundaries of knowledge, influence the future and create a lasting impact.

This post will be offered on a fixed-term contract until 31 March 2025

This is a full-time post – 100% full time equivalent

Key responsibilities

• Development of novel super resolution networks to enable high-resolution 3D coronary artery angiography in less than 1 minute.

• Development of end-to-end joint motion estimation and image reconstruction deep learning network for highly undersampled 3D coronary artery data.

• Validation of novel developments in phantoms, healthy subjects and patients.

• Achieve the above objectives in a coordinated way by effective teamwork and collaboration with colleagues.

• Contribute to the development and delivery of undergraduate and postgraduate teaching in the department

• Attend and, as appropriate, present research findings and papers at internal and external academic meetings, seminars and conferences and to contribute to the internal and external visibility of the Department.

• To contribute to the production of research reports and publications.

• To engage in integrative and original research and produce written research outputs, as set out in the research project.

• To undertake any other reasonable duties that are relevant with the Role Outline.

• Liaise with colleagues and students.

• Contribute to the integration and collaboration of research projects with other branches of the group and with external collaborators.

The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.

Skills, knowledge, and experience

Essential criteria

1. PhD awarded (or near completion) in Engineering, Physics, Computer Sciences or similar.

2. Experience in Machine Learning techniques

3. Experience in Magnetic Resonance image reconstruction (eg parallel imaging, compressed sensing) or inverse problems

4. Experience in MATLAB, Phyton, C ++ or similar

5. Presenting scientific research in the form of papers, posters and oral presentations

6. Working as part of a multidisciplinary research team, relying on and supporting others effectively

7. Excellent verbal and written communication skills

Desirable criteria

8. Experience in Magnetic Resonance physics

9. Experience in Magnetic Resonance pulse sequence development (Siemens environment preferred)

10. Experience in phantom, healthy subjects and patient scanning with MR imaging

11. Applying specialist knowledge in the context of medical imaging

Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the PhD award, the job title will become Research Associate and the salary will increase to Grade 6.

Further information

If further information is required, please contact [email protected]

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