<!--anchor--> <!--anchor--> Postdoctoral Research Associate in Human-Centred AI <!--anchor-->

This project is part of the UKRI Trustworthy Autonomous Systems (TAS) programme, funded through the UKRI Strategic Priorities Fund and delivered by the Engineering and Physical Sciences Research Council (EPSRC). The TAS programme brings together research communities and key stakeholders to drive forward cross-disciplinary, fundamental research to ensure that autonomous systems are safe, reliable, resilient, ethical, and trusted. 

This post is specifically associated with the UKRI Research Node on TAS Governance and Regulation – Better Governance by Design – led by Prof Subramanian Ramamoorthy from the School of Informatics, University of Edinburgh (UoE), in which Dr Hana Chockler is leading the direction of qualitative and quantitative responsibility. The post holder will be supervised by Dr Hana Chockler, and will work in close collaboration with other PDRAs in the Research Node.  

This Research Node is a collaboration with academics from the University of Edinburgh, University of Glasgow, Heriot-Watt University, King’s College London, University of Nottingham, and the University of Sussex. The researchers will also work closely with a diverse group of external project partners. The Node takes a multidisciplinary approach to its work, bringing together researchers with backgrounds in Computer Science and AI, Law, AI ethics, Social Studies of Information Technology and Design Ethnography. The diverse team offers a uniquely holistic perspective that combines technical, social science and humanities research to explore how to guarantee that autonomous systems can be trusted and integrated into society. 

The central purpose of the job is to develop methods for evaluation, testing and certification of human-centred AI systems involved in application areas such as AI-based medical diagnosis and autonomous mobility and transportation systems. A key challenge with these systems is systematic empirical evaluation of the full development and deployment pipeline and ensuring its compliance with legal and ethical frameworks for governance and regulation.  

The candidate is expected to have demonstrated a high level of practical skills, and in particular designing, implementing, and experimenting with AI systems, such as neural networks. The candidate is expected to work in close collaboration with the direction of testing and verification of autonomous systems. The focus will be on application domains such as medical diagnostics or autonomy.  

The ideal candidate would also have a strong track record of publication in leading conferences and journals in AI (e.g., IJCAI, AAAI, NeurIPS, ICML, ICLR) or in testing/verification (e.g., CAV, TACAS, ISSTA, ICSE, ASE). 

This post will be offered on a fixed-term contract terminating on 30/04/2024 

This is a full-time post - 100% full time equivalent

The successful candidate is expected to:  

• Planning and carrying out a programme of work appropriate to the research activity. 
• Fundamental as well as deliverable-driven research in a collaborative team environment. 
• Collaborating across the Governance and Regulation Node.  
• Liaising and collaborating, where appropriate, with related TAS Nodes and the Hub. 
• Engaging with our industrial collaborators. 
• Travelling to partner sites and project meetings. 
• Leading on the writing and submission process of papers at leading international conferences and journals. 
• Attending international conferences to present results. 
• Regularly reporting progress to the grant awarding agency (EPSRC).  

The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.  

Essential criteria  

1.     A PhD (or near completion) in AI, Verification, Software Engineering, or similar area. 

2.    Background and practical experience with programming, neural networks, evaluation, testing, and verification of emerging AI systems. 

3.    An excellent track record of publications in top tier conferences and/or journals in AI, verification or other related domains (e.g., AAAI, IJCAI, NeurIPS, CAV, TACAS, ISSTA, ICSE, ASE).

4.   Excellent proven programming and systems engineering skills.

5.   Ability to work effectively as part of a team, to meet deadlines, and to report on project progress.

Desirable criteria

1.    The PhD focussed on autonomous systems.

2.    Experience in an AI application domain of interest to the project such as medical diagnostics, autonomy in mobility and transportation systems, etc.

3.    Exposure to libraries and frameworks underpinning vision and robotics systems, and/or understanding of industrial processes for design and deployment of ML-based AI systems.

4.   Demonstrated experience of the development and management of projects involving multiple stakeholders.

5.   Ability to communicate complex information clearly, orally and in writing

6.   Experience of research in the broad area of the related project

7.   Preferably, experience in the specific area of the related project

8.   Proven expertise in the techniques needed to undertake the research in question

9.   Demonstrated quality of research performance

10. Ability to communicate complex information clearly, orally and in writing