Lecturer/Senior Lecturer/Reader/Professor in AI

We have thriving research programmes in global health, and health and social care. Within FoLSM, the School of Biomedical Engineering and Imaging Sciences is a cutting‑edge research and teaching School dedicated to development, translation and clinical application within medical imaging and computational modelling technologies. Our objective is to facilitate research and teaching guided by clinical questions aimed at novelty, understanding of physiology and pathophysiology as well as development of new diagnostic tools and therapies. The School consists of eight research departments: Cardiovascular Imaging, Cancer Imaging, Early Life Imaging, Imaging Chemistry & Biology, Biomedical Computing, Surgical & Interventional Engineering, Imaging Physics & Engineering and Digital Twins for Healthcare. Our staff and students comprise physicists, chemists, biologists, engineers, computer scientists, mathematicians and clinicians working together in a highly cross‑disciplinary way. The chemists and biologists develop new contrast agents and radiopharmaceuticals for molecular imaging; the physicists and engineers develop imaging hardware and instrumentation; and the computer scientists and mathematicians develop image processing and computational modelling methodologies; meanwhile, the clinicians apply them in a wide range of areas, such as cardiology, vascular surgery, cancer, neurology, paediatrics, nuclear medicine and radiology. This interdisciplinary group encourages the generation of projects far beyond classic research by combining the skills and equipment of basic scientists with those of clinical researchers. Our proactive approach to collaboration with other departments and Schools, both in basic sciences and clinical sciences, means that we widen the use of imaging and maximise the benefit to patients. There is a close and vital relationship in our work between problem solving in clinical and biomedical application areas and methodological research in the basic disciplines.

About the role: We are looking to appoint two exceptional academics at Lecturer, Senior Lecturer, Reader or Professor level (commensurate with experience and appointment level) to develop and lead ambitious, complementary research programmes in biomedical imaging methods. The posts are intended to strengthen core methodological expertise in areas including AI‑enabled image acquisition and reconstruction, physics‑informed AI and AI‑enabled quantitative imaging. We are particularly seeking candidates who can take full advantage of the extensive data generation capabilities we have, including multi‑coil k‑space data from 8 whole body MRI scanners, list mode data from 2 Total body PET systems and sinogram/projection data from a photon‑counting CT. Candidates will be favoured whose work can enhance existing strengths and strategic needs within the School notably cardiovascular MRI, but also including fetal and perinatal MRI, cancer imaging, multimodal imaging and related areas. Candidates do not need to cover all areas; we are seeking complementary appointments across the two posts. The post holders will work closely with colleagues across the Research Departments of Imaging Physics & Engineering, Cardiovascular Imaging, Biomedical Computing, Early Life Imaging and Digital Twins for Healthcare, and with clinical and industry partners. There will also be scope to extend methods to other areas aligned with School strategy.

The appointees will be expected to establish independent and externally funded research programmes, publish in high profile peer‑reviewed journals, supervise postgraduate students and research staff, and contribute to the School of BMEIS educational portfolio through undergraduate and postgraduate teaching. These are two full‑time posts (35 hours per week), and you will be offered indefinite contracts. Appointments will be made at Lecturer, Senior Lecturer, Reader or Professor level according to experience and track record.

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We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the person specification section of the job description. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible. Artificial intelligence (AI) is evolving rapidly, and we recognise its growing role in professional work. Applicants may use AI tools to support preparation of their application, for example to research the role or structure written responses. However, applications must reflect the applicant's own work and experience. AI tools should not be used during interviews or assessment activities unless this has been agreed in advance as a reasonable adjustment. Further guidance on the use of AI in recruitment can be found. We reserve the right to close adverts early due to the volume of applications we receive. While the closing date may change, all adverts will close at 23:59 to allow sufficient time for applications to be submitted on that day.

Essential criteria:

• PhD in relevant field or first degree in relevant field and extensive relevant experience
• Track record of high impact research, including significant methodological innovation, commensurate with opportunity and career stage, in at least one of the following: AI enabled acquisition and/or reconstruction of a tomographic imaging modality, imaging physics, acquisition, motion correction, innovation in accelerated image acquisitions with applications aligned with one of the core medical specialty strengths in the School.
• Expertise in at least one of the following: AI enabled acquisition and/or reconstruction of a tomographic imaging modality, imaging physics, data acquisition and scanner programming, motion correction, innovation in accelerated image acquisitions.
• Excellent written and oral communication skills.
• Excellent knowledge and understanding of cardiovascular MRI and relevant biomedical imaging, computational and translational requirements.
• Experience of grant writing and track record of successful research funding commensurate with opportunity/career stage and proposed level of appointment.
• Experience of writing and publishing papers in high quality peer reviewed journals.
• Team player with commitment to both lead and assist in interdisciplinary translational imaging projects as appropriate.

Desirable criteria:

• Relevant postgraduate certificate in higher education or equivalent.
• Established network of collaborations in interdisciplinary research, clinical translation and/or industry.
• Experience supervising junior researchers, postgraduate students and/or research staff, commensurate with career stage and proposed level of appointment.
• Experience teaching and lecturing at undergraduate/postgraduate level.
• Experience of one or more of MRI physics, MRI pulse programming, photon‑counting CT or total body PET data acquisition, Cardiac MRI, fetal MRI, cancer imaging, real‑time MRI.

The Faculty of Life Sciences & Medicine is one of the largest and most successful centres for research and education in the UK. The Faculty was created as a result of the merger of elements of the School of Biomedical Sciences with the School of Medicine. The merger brings together basic, translational and clinical scientists to provide new cross‑School research collaborations while optimising the deployment of teaching expertise across the Faculty. The Faculty has unparalleled expertise in basic, translational and clinical research; analytical and forensic science; asthma and allergy; biophysics and cell biology. At King's, we believe that the diversity of our community and a culture that is welcoming, open, inclusive and collaborative, are great strengths of the university.

Grade and Salary: Commensurate with experience and appointment level

Job ID: 155025