Assistant/Associate Professor in AI and Machine Learning

About the role

The Department of Computer Science and Technology at the University of Cambridge is recruiting a new faculty member as Assistant Professor or Associate Professor, depending on experience, to contribute to research and teaching in Artificial Intelligence and Machine Learning. The post is based in West Cambridge, is full-time and permanent, and starts on 1 September 2027 or as soon as possible thereafter. The successful candidate will be responsible to the Head of Department.

Key responsibilities

• Develop an independent research agenda in fundamental machine learning and lead an internationally competitive, externally funded research programme.
• Supervise research at Masters and PhD level, and contribute to undergraduate teaching in machine learning and mathematics.
• Develop innovative graduate content within the MPhil in Advanced Computer Science and help shape its curriculum.
• Secure research funding and build a world-class research team, supported by start-up costs covering PhD students, equipment and conferences.
• Collaborate across subdisciplines of computer science and with other fields such as mathematics, engineering, physics and chemistry.

Required profile

• Outstanding research credentials in fundamental machine learning, with an independent research agenda and a strong publication record.
• Evidence of community service and impact commensurate with career stage, and the ability to supervise Masters and PhD students.
• Ability to secure research funding and build a research team.
• Teaching experience is essential.

What we offer

• Salary of £48,337 to £61,165 (Assistant Professor) or £64,878 to £68,817 (Associate Professor).
• A reduced teaching load in the first year, averaging under 30 hours of lecturing per year.
• Statutory sabbatical leave: one term of research leave on full pay for every six terms of service.
• Administrative support for research management, funding, communications, finance and recruitment.

Applications are made online with a CV, research statement, teaching statement and cover letter, quoting reference NR49860. Interviews are held in Cambridge on 3 and 4 March 2027; the closing date is 15 December 2026.