University Assistant or Associate Professor (Honorary Consultant) in Artificial Intelligence for Cli

University of Cambridge; Cambridge; On-site; GBP 80,000 - 110,000; Full time

Job summary

A prestigious university in Cambridge seeks a Clinical Assistant Professor, Associate Professor, or Clinical Professor in Radiology. The role focuses on building clinical imaging research portfolios emphasizing AI and machine learning integration. Applicants should be clinically qualified, specialized, and have a strong research track record in these areas. The position offers a dynamic environment with opportunities for innovation in patient care.

Qualifications

• Clinically qualified in Radiology or Nuclear Medicine.
• Experience in research related to AI, ML, or image analysis.

Responsibilities

• Build a portfolio of clinical imaging research projects.
• Integrate imaging data with other sources to enhance disease stratification.

Skills

Clinical qualifications

AI research

ML experience

Image analysis

Education

Medical degree in Radiology or Nuclear Medicine

Job description

Overview

The Department of Radiology is an internationally competitive department undertaking innovative research in medical imaging. It consists of a multidisciplinary team of dedicated academic radiologists and imaging scientists, with active doctoral and post-doctoral research training programmes. The department undertakes world-leading research in several areas including Metabolic Imaging, MRI, PET, and image analysis.

This full-time university post is based in the Academic Department of Radiology with clinical sessions at Cambridge University NHS foundation Trust Hospital. Our artificial intelligence (AI), machine learning (ML) and image analysis programme is growing and covers many modalities. This is a strategic area for the Department to develop in the coming decade, and is key for many biomedical developments across the campus.

Responsibilities

• The successful applicant will be supported in building a portfolio of clinical imaging research projects which have a significant component of AI, ML or image analysis methods within them.
• Integration of imaging data with other data sources - such as clinical data, tissue, or liquid biomarkers - will be used to better stratify disease and predict or detect response to treatment.

Qualifications and experience

• The applicant will ideally be clinically qualified, specialised in radiology or nuclear medicine, who has undertaken significant research in the areas of AI, ML, or image analysis and is currently working actively in a clinical imaging environment.
• The appointee will have a strong track record in these areas and a growing reputation as a leader in the field. It is expected that the appointee will broaden the research in the department into new, innovative areas for patient benefit.

Appointment and conditions

Once an offer of employment has been accepted, the successful candidate will be required to undergo a health assessment. This appointment also requires an Honorary Clinical Contract.

How to apply

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online. Please ensure that you upload your Curriculum Vitae (CV), a covering letter and research publication list, along with details of three referees, one of which must be the most recent employer, no later than Thursday 25 September 2025. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.

Informal enquiries are welcome via email to Professor Ferdia Gallagher: [e-mail].

Levels and how to apply for professor positions

This opportunity is open to appointment at Clinical Assistant Professor, Clinical Associate Professor, or Clinical Professor level, depending on experience and qualifications. If you are applying for the Clinical Professor level, please apply through https://www.cam.ac.uk/jobs/term/Professorships-and-Directorships. Please note only one post is available and will be offered at a level that reflects the merit of the successful candidate.

Please quote reference RQ47248 on your application and in any correspondence about this vacancy.

Equality and eligibility

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society. The University has a responsibility to ensure that all employees are eligible to live and work in the UK.