Postdoctoral Researcher in Machine Learning analysis of MRI

Cambridge University Hospitals NHS Foundation Trust
Newtown
1 month ago
Applications closed
Postdoctoral Researcher in Machine Learning analysis of Magnetic Resonance Imaging (MRI)

Applications are invited for an enthusiastic and motivated Post‑doctoral Researcher to join the Lysosomal Disorders Unit at Cambridge University Hospitals NHS Foundation Trust. The post (Band 7) is funded by an award from industry, for a term of two years. The successful applicant will work as part of a team of clinical and imaging specialists.


The ethically‑approved award is to develop a machine‑learning technique to simulate quantitative Dixon fat/water images from a database of traditional T1 and T2‑weighted MR images of muscle. A large training set of Dixon fat/water images, paired with T1 and T2‑weighted images of muscle and other structures, is available locally and from collaborators. The ultimate purpose is to develop a technique to monitor disease progression and response to treatment in genetic diseases of muscle, in which fat replacement is a hallmark of disease.


Such a technique may have wider application to other organs, tissues and disease states. This is a collaborative translational research post focussing on the development of state‑of‑the‑art machine/deep learning‑based medical image analysis methods for MRI. The specific focus is to develop novel biomarkers of fat infiltration in muscle and other tissues for use in real‑world clinical settings.


You will have a PhD in a relevant subject such as computer science or engineering, together with essential experience in advanced analysis of medical images, particularly machine‑learning analysis of musculoskeletal MR. Experience in manual and machine‑learning segmentation of anatomic structures is highly desirable. A substantial publication record in the field is valued. Excellent organisational skills and the ability to work as part of a team, as well as independently, are also essential.


Our Trust

Cambridge University Hospitals (CUH) NHS Foundation Trust comprises Addenbrooke's Hospital and the Rosie Hospital in Cambridge. With over 13,000 staff and over 1,100 beds the priorities of the Trust focus on a quality service which is all about people – patients, staff and partners. Recognised as providing ‘outstanding’ care to our patients and rated ‘Good’ overall by the Care Quality Commissioner, is testament to the skill and dedication of the people who work here. CUH's values – Together – Safe, Kind, Excellent – are at the heart of patient care, defining the way all staff work and behave. The Trust provides accessible high‑quality healthcare for the local people of Cambridge, together with specialist services, dealing with rare or complex conditions for a regional, national and international population.


CUH is committed to promoting a diverse and inclusive community – a place where we can all be ourselves. We value our differences and fully advocate and support an inclusive working environment where every individual can fulfil their potential. We want to ensure our people are truly representative of all the communities that we serve. We welcome applications for all positions in the organisation irrespective of people's age, disability, ethnicity, race, nationality, gender identity, sex, sexual orientation, religion or belief, marriage and civil partnership status, or pregnancy and maternity status or social economic background.


#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.

Where to Advertise AI Jobs in the UK (2026 Guide)

Advertising AI jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly informed and in demand across multiple sectors simultaneously. General job boards reach a broad audience but lack the specificity that AI professionals expect — and the filtering mechanisms they rely on. Specialist platforms, direct outreach and academic channels each serve a different part of the market. This guide, published by ArtificialIntelligenceJobs.co.uk, covers where to advertise AI roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about time-to-hire across different role types.

New AI Employers to Watch in 2026: UK and Global Companies Reshaping AI Careers

The artificial intelligence job market in the UK is evolving at an extraordinary pace. With record-breaking investment, government backing, and a surge in enterprise adoption, the landscape of AI employers is shifting rapidly. For candidates exploring opportunities on ArtificialIntelligenceJobs.co.uk, understanding who is hiring next is just as important as understanding what skills are in demand. In this article, we explore the new and emerging AI employers to watch in 2026, focusing on organisations that have recently secured funding, won major contracts, or expanded their UK footprint. From cutting-edge startups to global giants doubling down on Britain, these companies represent the next wave of AI career opportunities.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.