Postdoctoral Researcher in Machine Learning analysis of MRI
| Dyddiad hysbysebu: | 03 Mawrth 2026 |
|---|---|
| Cyflog: | Heb ei nodi |
| Gwybodaeth ychwanegol am y cyflog: | £47,810 - £54,710 p.a. pro rata |
| Oriau: | Llawn Amser |
| Dyddiad cau: | 02 Ebrill 2026 |
| Lleoliad: | Cambridge, CB2 0QQ |
| Cwmni: | Cambridge University Hospitals NHS Foundation Trust |
| Math o swydd: | Cytundeb |
| Cyfeirnod swydd: | 7832451/180-RD-264062 |
Crynodeb
A Vacancy at Cambridge University Hospitals NHS Foundation Trust.
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.
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.
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.
Excellent organisational skills and the ability to work as part of a team, as well as independently, are also essential.
Please see the attached Applicant Information Pack for key duties and responsibilities.
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 1100 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.
Please see the attached Applicant Information Pack (combined Job Description and Person Specification) for key duties and responsibilities.
Informal enquiries directed to Dr. Patrick Deegan (patrick.deegan1@nhs.net) are encouraged.
This vacancy will close at midnight on 9th March 2026
Interviews are due to be held on 26th or 27th March 2026
Benefits to you
At Cambridge University Hospitals, we want to do all we can to support good working days. We offer development opportunities and a wide range of benefits, including on-site leisure facilities, shopping concourse and day nurseries. Our good work programme currently includes providing reduced cost Stagecoach bus travel to and from Cambridge University Hospital site. Park and Ride bus journeys between Babraham Road and Trumpington sites are free, as is the route to and from Cambridge train station and our hospitals. We also subsidise the cost of parking on site for eligible staff.
On CUH campus, hot food is available 24/7 and at a reduced cost for colleagues. Recently we launched the first of our staff pod break spaces. Located in the Deakin Centre, we have a purpose-created colleague-only café, with free tea and coffee, a break space and private outside area for colleagues to rest, refuel and recharge. Just one of the ways we are working hard to support good working days at CUH.
CUH is committed to assisting employees in achieving a good work-life balance irrespective of role or personal circumstances. Flexible arrangements may include, but are not limited to, part-time working, job-share, term-time working and flexible start and finish times.
Please note if you would like to discuss the required hours of this role further, you should approach the contact given. In some cases, alternative working hours will be considered.
We welcome applications from the Armed Forces.
This advert closes on Monday 9 Mar 2026
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.
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.
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.
Excellent organisational skills and the ability to work as part of a team, as well as independently, are also essential.
Please see the attached Applicant Information Pack for key duties and responsibilities.
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 1100 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.
Please see the attached Applicant Information Pack (combined Job Description and Person Specification) for key duties and responsibilities.
Informal enquiries directed to Dr. Patrick Deegan (patrick.deegan1@nhs.net) are encouraged.
This vacancy will close at midnight on 9th March 2026
Interviews are due to be held on 26th or 27th March 2026
Benefits to you
At Cambridge University Hospitals, we want to do all we can to support good working days. We offer development opportunities and a wide range of benefits, including on-site leisure facilities, shopping concourse and day nurseries. Our good work programme currently includes providing reduced cost Stagecoach bus travel to and from Cambridge University Hospital site. Park and Ride bus journeys between Babraham Road and Trumpington sites are free, as is the route to and from Cambridge train station and our hospitals. We also subsidise the cost of parking on site for eligible staff.
On CUH campus, hot food is available 24/7 and at a reduced cost for colleagues. Recently we launched the first of our staff pod break spaces. Located in the Deakin Centre, we have a purpose-created colleague-only café, with free tea and coffee, a break space and private outside area for colleagues to rest, refuel and recharge. Just one of the ways we are working hard to support good working days at CUH.
CUH is committed to assisting employees in achieving a good work-life balance irrespective of role or personal circumstances. Flexible arrangements may include, but are not limited to, part-time working, job-share, term-time working and flexible start and finish times.
Please note if you would like to discuss the required hours of this role further, you should approach the contact given. In some cases, alternative working hours will be considered.
We welcome applications from the Armed Forces.
This advert closes on Monday 9 Mar 2026