Research Fellow
| Dyddiad hysbysebu: | 11 Chwefror 2026 |
|---|---|
| Cyflog: | £36,636 i £44,746 bob blwyddyn |
| Oriau: | Llawn Amser |
| Dyddiad cau: | 18 Chwefror 2026 |
| Lleoliad: | Southampton, Hampshire |
| Gweithio o bell: | Ar y safle yn unig |
| Cwmni: | University of Southampton |
| Math o swydd: | Cytundeb |
| Cyfeirnod swydd: | 3337126FP |
Crynodeb
Section
Vision, Learning and Control
Location:
Highfield Campus
Salary
£36,636 to £44,746
Full Time Fixed Term (1 Year)
Closing Date:
Wednesday 18 February 2026
Reference
3337126FP
Research Fellow
Research Fellow in Medical Machine Learning (Cystic Fibrosis)
The University of Southampton is seeking to appoint a Research Fellow in Medical Machine Learning to work on an externally funded collaborative research project focused on chest X-ray analysis in cystic fibrosis.
The post will be based in the School of Electronics and Computer Science, Faculty of Engineering and Physical Sciences, and will involve close collaboration with Paediatric Respiratory Medicine at University Hospital Southampton. The role is fully externally funded via a recharge from a University Hospital Southampton Principal Investigator fund.
The role
Working with appropriate guidance and supervision, the post holder will undertake applied research in machine learning and artificial intelligence for medical imaging. The focus of the role is the development, validation and interpretation of machine-learning models applied to large-scale clinical chest X-ray datasets, with the aim of improving disease characterisation and clinical decision-making in cystic fibrosis.
The post holder will be expected to:
Design, implement and evaluate machine-learning and deep-learning models for medical imaging
Work closely with clinical collaborators to ensure clinical relevance and robustness
Publish high-quality research outputs in peer-reviewed journals
Present findings at national and international conferences
Contribute to future funding applications in clinical artificial intelligence and digital health
About you
You will have substantial practical experience in machine learning, data science or artificial intelligence, supported by a strong theoretical understanding. This will normally have been gained through relevant research or professional experience and/or postgraduate qualifications. Near-completion or completion of a PhD in a relevant discipline (e.g. machine learning, computer science, engineering, data science) is desirable.
You will be able to work effectively across disciplinary boundaries, communicate complex technical ideas clearly, and manage your research activities within agreed objectives and timelines.
Additional information
The role involves working with sensitive clinical imaging data. An honorary contract / Letter of Access with University Hospital Southampton will be required. Occasional travel between University and NHS sites may be necessary.
Apply by uploading your CV and a cover letter detailing how your skills and experience match the requirements of the role.
We aim to create an environment where everyone can thrive and are proactive in fostering a culture of inclusion, respect and equality of opportunity. We welcome applications from candidates who are committed to helping us create an inclusive work environment. We particularly encourage applications from people who identify with one or more of the following: Black, Asian, a minority ethnic background, coming from a lower socio-economic background, LGBTQ+, a woman or having a disability as these identities are currently underrepresented in our working community.
The University of Southampton is committed to sustainability and being a globally responsible university and has been awarded the Platinum EcoAward.
Vision, Learning and Control
Location:
Highfield Campus
Salary
£36,636 to £44,746
Full Time Fixed Term (1 Year)
Closing Date:
Wednesday 18 February 2026
Reference
3337126FP
Research Fellow
Research Fellow in Medical Machine Learning (Cystic Fibrosis)
The University of Southampton is seeking to appoint a Research Fellow in Medical Machine Learning to work on an externally funded collaborative research project focused on chest X-ray analysis in cystic fibrosis.
The post will be based in the School of Electronics and Computer Science, Faculty of Engineering and Physical Sciences, and will involve close collaboration with Paediatric Respiratory Medicine at University Hospital Southampton. The role is fully externally funded via a recharge from a University Hospital Southampton Principal Investigator fund.
The role
Working with appropriate guidance and supervision, the post holder will undertake applied research in machine learning and artificial intelligence for medical imaging. The focus of the role is the development, validation and interpretation of machine-learning models applied to large-scale clinical chest X-ray datasets, with the aim of improving disease characterisation and clinical decision-making in cystic fibrosis.
The post holder will be expected to:
Design, implement and evaluate machine-learning and deep-learning models for medical imaging
Work closely with clinical collaborators to ensure clinical relevance and robustness
Publish high-quality research outputs in peer-reviewed journals
Present findings at national and international conferences
Contribute to future funding applications in clinical artificial intelligence and digital health
About you
You will have substantial practical experience in machine learning, data science or artificial intelligence, supported by a strong theoretical understanding. This will normally have been gained through relevant research or professional experience and/or postgraduate qualifications. Near-completion or completion of a PhD in a relevant discipline (e.g. machine learning, computer science, engineering, data science) is desirable.
You will be able to work effectively across disciplinary boundaries, communicate complex technical ideas clearly, and manage your research activities within agreed objectives and timelines.
Additional information
The role involves working with sensitive clinical imaging data. An honorary contract / Letter of Access with University Hospital Southampton will be required. Occasional travel between University and NHS sites may be necessary.
Apply by uploading your CV and a cover letter detailing how your skills and experience match the requirements of the role.
We aim to create an environment where everyone can thrive and are proactive in fostering a culture of inclusion, respect and equality of opportunity. We welcome applications from candidates who are committed to helping us create an inclusive work environment. We particularly encourage applications from people who identify with one or more of the following: Black, Asian, a minority ethnic background, coming from a lower socio-economic background, LGBTQ+, a woman or having a disability as these identities are currently underrepresented in our working community.
The University of Southampton is committed to sustainability and being a globally responsible university and has been awarded the Platinum EcoAward.
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