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"Senior Researcher in Healthcare AI"

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Senior Researcher in Healthcare AI

Senior Researcher in Healthcare AI

University of Oxford - NDM Experimental Medicine

Location: Oxford

Salary: £49,119 to £58,265 p.a.

Hours: Full Time

Contract Type: Fixed-Term/Contract

Placed On: 9th September 2025

Closes: 8th October 2025

Job Ref: 181767

John Radcliffe Hospital, Oxford

About the role

We are seeking a talented Postdoctoral Researcher with expertise in healthcare AI to join the Modernising Medical Microbiology (MMM) Unit at the University of Oxford. This is an exciting opportunity to lead innovative research at the interface of AI and clinical medicine, working within a 40-strong interdisciplinary team spanning AI, statistics, microbiology, epidemiology, public health, and bioinformatics.

You will apply advanced AI methods - from classical machine learning to large language models and agent-based AI - on large-scale healthcare datasets, including structured records and clinical free text. Projects will focus on improving infection diagnosis and treatment, detecting outbreaks in real time, and optimising hospital care pathways.

The post is embedded in two major National Institute for Health Research-funded initiatives: the Oxford Biomedical Research Centre and the NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance. You will also help evaluate AI tools in real-world healthcare settings, supervise PhD students, and contribute to shaping the future direction of AI in the Unit.

This post is full time and fixed term until 31/03/2028. Part-time working will be considered (minimum 0.8 FTE, 30 hours per week minimum).

About you

You’ll have a PhD (or equivalent experience) in a relevant field, with demonstrable expertise in AI and machine learning – from classical approaches to large language models. You are proficient in Python and key ML libraries (e.g. scikit-learn, PyTorch, LLM APIs), and you have a track record of applying these methods to deliver reproducible, high-quality analyses. You thrive when working independently and collaboratively, enjoy engaging with colleagues from different disciplines, and have excellent organisational, communication, and interpersonal skills.

You will bring: Strong experience applying AI methods to complex data, ideally healthcare data; A record of high-quality publications and presentations to varied audiences; The ability to supervise PhD students and support colleagues; A flexible and proactive attitude, with initiative to develop new approaches and strategies; A keen interest in biomedical science and medicine.

Experience in applying AI to large-scale healthcare datasets, contributing to grant proposals, or deploying AI tools in real-world applications would be highly valuable. The successful candidate will be required to access data held by the UK Health Security Agency in order to undertake this role. In addition to the standard University pre-employment checks for appointment, the successful candidate must also satisfactorily obtain UK Health Security Agency clearance in order to access national data. Applications from candidates who do not fulfil the essential criteria will be considered for appointment at Grade 7 with a salary range of £39,424- £47,779 per annum with amended duties and responsibilities.

About us

The MMM Unit is based at the Big Data Institute and John Radcliffe Hospital. We work closely with the NHS, the UK Health Security Agency, and other partners to ensure research translates rapidly into clinical and public health benefit. If you’re passionate about using AI to solve real-world health challenges, we’d love to hear from you.

Application Process

Applications for this vacancy are to be made online via the above ‘Apply’ button. You will be required to upload a supporting statement and CV as part of your online application. Only applications received before 12:00 midday on Wednesday 8/10/2025 will be considered. Contact Person: HR Team; Closing Date & Time: 08-Oct-2025 12:00; Pay Scale: RESEARCH GRADE 8; Contact Email: exp.med-hr@ndm.ox.ac.uk

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