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College Lane Campus, Hatfield

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"Senior Fellowship in AI for Health, Medicine and Life Sciences"

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Senior Fellowship in AI for Health, Medicine and Life Sciences

SBU/Department: School of Health, Medicine and Life Sciences
FTE: 1.0 FTE (37 hours per week)
Duration of Contract: Fixed Term (2 years)
Salary: UH8 £46,049 pa to £58,225 pa by annual increments on achieving designated skills and experience
Annual Leave: 35 days plus standard public holidays and an additional 4 days, including the closure of our office between Christmas and New Year
Location: College Lane Campus, Hatfield

This senior fellowship offers a high-impact opportunity to lead the integration of AI across health, medicine, and life sciences. This role is ideal for an experienced researcher eager to advance digital transformation, build institutional AI capability, and make a lasting impact on healthcare and biomedical innovation.

Main duties and responsibilities

You will drive strategic initiatives, shaping AI adoption in areas such as predictive diagnostics, personalised medicine, and clinical trial optimisation, while collaborating with internal and external stakeholders, NHS partners, and industry to deliver demonstrator projects with tangible outcomes. In addition to research leadership, you will mentor junior colleagues, integrate AI strategies into grant proposals and fellowship applications by research staff, lead training on AI and data governance, and contribute to policy and ethical frameworks for responsible AI use.

Skills and experience required

We are seeking an accomplished AI researcher with substantial experience leading research teams and projects, mentoring junior staff, and managing collaborative partnerships with academic and external organisations. You will have a strong record of scholarly work, successful funding applications, and presenting research at local, national and international forums. PhD supervision and public engagement experience are also desirable. You will bring deep expertise in ML/DL techniques, NLP, computer vision, and predictive modelling, alongside excellent IT, analytical, interpersonal and communication skills in spoken and written English. You must be able to collect, process and present data with excellent analytical skills, be methodical, adaptable and proactive to team and workload requirements, work accurately under pressure to tight deadlines, work effectively in teams, and be committed to continuous learning and development while handling sensitive data with confidentiality and care. You will have a can-do attitude to problem-solving, have tact and diplomacy, as well as the initiative to learn new skills and demonstrate continuous development.

Qualifications required

You will have a degree or equivalent Level 6 Qualification, or a higher qualification in a relevant discipline. You will also have a PhD (or equivalent) in AI, Data Science, Computer Science, Biomedical Engineering, or a related field, or equivalent experience applying AI/ML to healthcare or biomedical data.

Please view the job description and person specification for a full list of the duties and essential criteria. Please attach a personal statement showing clearly how your skills and experience match the person specification.

Internal applicants – please ensure you apply via your employee self-service portal.

An appointment to this role may require an Academic Technology Approval Scheme (ATAS) certificate.

Please note, this post cannot be visa sponsored unless you can evidence a PhD / Doctorate.

Contact Details/Informal Enquiries: Rich Callaghan (Associate Dean for Research) r.callaghan@herts.ac.uk

Closing Date: 26 March 2026
Interview Date: TBC
Reference Number: REQ000549

Our vision is to transform lives: UH is committed to Equality, Diversity, and Inclusion and building a diverse community. We welcome applications from suitably qualified and eligible candidates regardless of their protected characteristics and recognise that there are different ways applicants may achieve the criteria in this document. We offer a range of employee benefits, including generous annual leave, flexible location opportunities within the UK, discounted Sports Village memberships, free Active Staff sessions, personal and professional development, and family-friendly policies. #GoHerts

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