University Assistant/Associate Professor in Artificial Intelligence and Machine Learning

The Department of Computer Science and Technology is seeking to recruit a new faculty member at the Assistant Professor/Associate Professor level who will contribute to research and teaching in Artificial Intelligence and Machine Learning.

We are looking for a candidate with outstanding research credentials in fundamental machine learning, who is actively questioning and rethinking the current status-quo in AI and who will make significant contributions to the next generation of novel models, abstractions and architectures.  Example specialist areas may include, but are not limited to, post-transformer architectures, continuous learning models, probabilistic machine learning and uncertainty quantification, causal machine learning, learning theory, methods bridging statistical learning and symbolic reasoning, probabilistic numerics, robust and certifiable machine learning, and foundational ML methods for scientific discovery. 

Candidates will have evidence of an independent research agenda, a strong publication record, international visibility, documented evidence of community service and evidence of impact commensurate with career stage and able to supervise research at both Masters and PhD level.  Teaching experience is essential and the appointee will be expected to develop innovative graduate content within the MPhil in Advanced Computer Science, and advance the curriculum and contribute to undergraduate teaching in machine learning and mathematics.

The ability to secure research funding to support their vision and build a world-class team is essential. We welcome applications from researchers with interdisciplinary interests who will collaborate across different subdisciplines in Computer Science and with other academic fields (e.g., mathematics, engineering, physics, chemistry, etc.).

The Department is strongly research-oriented and has long-standing strengths across a range of topics in computer science. In recent years the department has focused on building a strong presence within machine learning. The Department benefits from the machine learning ecosystem across Cambridge with strong collaborations with especially Engineering, Mathematics and Physics.

All members of the Department are supported in developing their research leadership. We provide administrative support across research management, funding, communications, finance, and recruitment, and benefit from strong university-wide initiatives in commercialization, collaboration, ethics, and interdisciplinary centres.

Please ensure that you upload the application documentation in PDF format as follows:

• Curriculum vitae, including a complete list of publications.
• Research statement.
• Please provide one or two examples of research work that you feel best represent you as a researcher and your contributions to the field. These may be publications or other research outputs. You may upload a pdf of the work, or simply include references at the end of your research statement.
• Teaching statement.
• Cover letter.

Please see the Further Particulars document for details of expectations of research, teaching, and other aspects of the role. Click the 'Apply' button above. 

To apply online for this vacancy and to view further information about the role, please click the 'Apply' button above.

Interviews will take place in Cambridge on 3rd and 4th March 2027.

The successful candidate will join the Department on 1st September 2027, or as soon as possible thereafter.

Interested applicants are encouraged to make informal enquiries about the post to Professor Robert Mullins at aiml-enquiries@cst.cam.ac.uk

Please quote reference NR49860 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

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