Associate Professor in Medical Artificial Intelligence (AI) and Data Science (ATR1731)

UEA
Norwich
2 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist KTP Associate - Salford

Data Scientist KTP Associate - Salford

Data Scientist KTP Associate - Salford

Data Scientist KTP Associate - Salford

Data Scientist KTP Associate - Salford

Data Scientist KTP Associate - Salford

Associate Professor in Medical Artificial Intelligence (AI) and Data Science (ATR1731)

Salary will be £58,225 per annum, with an annual increment up to £67,468 per annum


About the Role:

Faculty of Medicine and Health Sciences


Norwich Medical School


Associate Professor/Senior Lecturer in Medical Artificial Intelligence (AI) and Data Science (2 Posts)


Ref: ATR1731


Salary on appointment will be £58,225 per annum, with an annual increment up to £67,468 per annum.


The Norwich Medical School is looking to appoint two Associate Professors/Senior Lecturers in Medical Artificial Intelligence (AI) and data science on our Academic Teaching and Research (ATR) pathway. You will be involved in research and innovation, and in the development and delivery of teaching. We are particularly interested in candidates that may be able to contribute to expanding our research and teaching portfolio in areas of growth such as Artificial Intelligence within the medicine and healthcare sector, and areas of excellence including data science.


You will be expected to have a strong recent track record of attracting research funding from government or industry in areas linked to AI, data science or related domains, particularly in application to medicine and health sciences, and will also have a strong portfolio of recent research publications in prestigious international journals. It is also desirable that you have an extensive network of national and international collaborators from academia, government and industry.


A PhD (or equivalent qualification) in a relevant subject area with proven experience of high-quality undergraduate and postgraduate teaching is essential. This includes experience of teaching and research in Artificial Intelligence and its application to Medicine and Healthcare, ideally with a research focus in areas such as machine learning, medical image analysis, clinical natural language processing, or AI for precision medicine. The successful candidate will contribute to developing and delivering innovative interdisciplinary teaching at the interface of computing and health sciences, and to advancing research that translates AI innovations into clinical impact, therefore experience in module development in this area would be desirable.


You may have evidence of leadership of course development and the use of a range of both innovative and traditional pedagogical practices. Experience of PhD supervision is essential.


As part of the wider UEA and Norwich Research Park ecosystem, the School enjoys close collaborations with School of Computing Science and the School of Health Sciences as well as the NNUH which is one of the UK’s largest hospitals with over 60 specialist services in situ. The wider Norwich Research Park is one of the world’s largest concentrations of research institutions in biological sciences with medical technology as one of the key fields of research.


These full‑time posts are available on an indefinite basis.


We value diversity and are committed to creating an inclusive culture where everyone can thrive. We particularly welcome applicants with the protected characteristics of disability, race (Black, Asian and minority ethnic), and sex (female), for this post, as they are currently underrepresented at this level within the School. Appointment will be made on merit and all applicants will be scored against the same criteria.


Benefits include:

  • 44 days annual leave inclusive of Bank Holidays and University Customary days (pro rata for part-time).
  • Family and Work‑life balance policies including hybrid working and considerable maternity, paternity, shared parental leave and adoption leave.
  • Generous pension scheme with life cover for dependants, plus incapacity cover.
  • Health and Wellbeing: discounted access to Sportspark facilities, relaxation rooms, 320 acres of rolling parkland, wellbeing walks, Wellbeing Ambassador network, on‑campus medical centre including NHS Dentist, Occupational Health and a 24/7 Employee Assistance Programme.
  • Campus Facilities: Sportspark, library, nursery, supermarket, post office, bars and catering outlets.
  • Exclusive shopping discounts to help cut the cost of household bills, childcare salary sacrifice scheme, Cycle to Work scheme and public transport discounts.
  • Personal Development: unlimited access to LinkedIn Learning courses, specialist advice and training from our Organisational Development and Professional Learning Team.

Closing date: 5 January 2026


The University holds an Athena Swan Silver Institutional Award in recognition of our advancement towards gender equality.


Further Information

For further information, including the Job Description and Person Specification, please see the attached Candidate Brochure.


For an informal discussion about the post please contact the Head of School PAvia


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.