Research Associate/Research Fellow in Safe AI Systems

University of York - Computer Science

Imphal West District

On-site

Full time

14 days+
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Job description

  • 15225 Research Associate in Safe AI Systems.pdf (PDF, 405.04kb)
  • 15225 Research Fellow in Safe AI Systems.pdf (PDF, 412.04kb)

Department

Computer Science

Salary

£37,694 to £56,535 per year

Grade

Grade 6/7

Contract status

Fixed term

Hours of work

Full-time

Based at

University of York campus

Interview date

w/c 28th September

Posted Date

29/07/2026

Apply by

09/09/2026

Job Reference

15225

  • 15225 Research Associate in Safe AI Systems.pdf (PDF, 405.04kb)
  • 15225 Research Fellow in Safe AI Systems.pdf (PDF, 412.04kb)
Role Description

Department

This role will give you the opportunity to help achieve the safe and responsible uptake of AI and Autonomous Systems (AI/AS) in application domains including automotive, healthcare, maritime and rail. You will be part of the Centre for Assuring Autonomy (CfAA) that pioneered approaches to assuring AI and autonomous systems.

Role

This role offers the opportunity to both accelerate the adoption of these core ideas and to further advance them. Building on our Guidance on the Safety Assurance of Autonomous Systems in Complex Environments (SACE), you will conduct research using a whole-systems approach to the design, analysis and assurance of AI/AS from engineering and sociotechnical viewpoints. A key focus area will be safety cases for AI/AS, specifically how they are developed and reviewed throughout their lifecycle. You will also have the opportunity to engage with PhD students from the UKRI AI Centre for Doctoral Training in Safe Artificial Intelligence Systems (SAINTS) through joint research projects, training activities and co-supervision.

We are seeking researchers who can demonstrate the capacity to push the boundaries of safety science for AI/AS, rather than simply applying existing techniques.

Skills, Experience & Qualification Needed
Grade 6 - Research Associate
  • First degree in Computer Science, Engineering, Psychology or cognate discipline
  • PhD, or in final stages thereof, in Computer Science, Engineering, Psychology, Safety Science or cognate discipline, or equivalent experience
  • Knowledge of safety science and system safety, with the ability to conduct high-quality research
  • Knowledge of AI and autonomous systems, specifically their design and/or use within safety-critical environments
  • Ability to work as part of a diverse and multidisciplinary team
  • Collaborative ethos
Grade 7 - Research Fellow
  • First degree in Computer Science, Engineering, Psychology or cognate discipline
  • PhD in Computer Science, Engineering, Psychology, Safety Science or cognate discipline, or equivalent experience
  • Knowledge of safety science and system safety, with the ability to conduct high-quality research
  • Knowledge of AI and autonomous systems, specifically their design and/or use within safety-critical environments
  • Ability to lead and/or take responsibility for a small research project or identified parts of a large project
  • Ability to supervise the work of others, for example in research teams or projects
  • Proven ability to attract and obtain external research funding
  • Collaborative ethos

Interview date: w/c 28th September 2026

For informal enquiries: please contact Professor Ibrahim Habli on Ibrahim.Habli@york.ac.uk

The University strives to be diverse and inclusive – a place where we can ALL be ourselves.

We particularly encourage applications from people who identify as Black, Asian or from a Minority Ethnic background, who are underrepresented at the University.

We offer family friendly, flexible working arrangements, with forums and inclusive facilities to support our staff. #EqualityatYork

As a Disability Confident employer, we will ensure that a fair and proportionate number of disabled applicants that meet the minimum (essential) criteria for each position will be offered an interview. Read more about the University of York's commitments under the Disability Confident scheme.

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