Senior Machine Learning Scientist

Applications are invited for a Senior Machine Learning Scientist to join the Medical Statistics group, with a combination of research and teaching responsibilities.

The successful applicant will conduct research activities with a variety of research groups in the Nuffield Department of Primary Health Care Sciences, and take a senior role in postgraduate and other teaching. Research responsibilities will include supporting and leading data analysis, seeking research funding, and providing specialist expertise in machine learning to colleagues. Teaching responsibilities will include creation and delivery of classes in machine learning for doctors, other health professionals and health researchers. Other teaching responsibilities are likely to include module coordination and marking, and supervising graduate students.

You will hold a doctoral degree (e.g. PhD) and have a strong publication record in medical research. You should be prepared to take a senior role as described in the job description. Candidates unsure if they are qualified for the senior role are invited to apply; there is flexibility to make an appointment at a more junior level, if no suitable senior applicant is found.

You will be based in the Radcliffe Primary Care Building in Oxford as your normal place of work, although some degree of remote working can be negotiated. A full-time post is available, but we have flexibility to offer a part-time post if requested by the successful candidate.

The position is fixed-term for three years in the first instance. For further information or discuss the post please contact Richard Stevens, at 

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“Committed to equality and valuing diversity”

You will be required to upload a CV and Supporting Statement as part of your online application. The Supporting Statement should include a cover letter and should also clearly describe how you meet each of the selection criteria listed in the job description. Click 

for information and advice on writing an effective Supporting Statement.

The closing date for applications is 12 noon on 22 April 2024

Interviews are expected to be held during the week commencing 6 May 2024.