Research Associate/Research Fellow in Safe AI Systems

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 & Qualifications 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 .

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.

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