University of Edinburgh
The 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.
The appointee to this post will work with industry partners on the development of case studies in the governance of Trustworthy Autonomous Systems. The appointee will be supervised by Prof Stuart Anderson, and also work closely with Prof Robin Williams, Prof Burkhard Schafer, and Prof Subramanian Ramamoorthy who leads the Research Node. This post will be based in the School of Informatics, University of Edinburgh.
The background required for the post could range from:
A PhD in in AI, Machine Learning or similar area together with a strong interests in the embedding of these techniques in real use contexts and the regulation of this embedding process.
To: A PhD with a focus on the social, organisational or legal aspects of socio-technical systems together with proven evidence of programming ability and understanding of AI and Machine Learning with some practical experience of using such systems.
Knowledge, skills and experience
Essential knowledge, skills and experience are:
A PhD (or near completion) in AI, Machine Learning, or social, organisational or legal aspects of socio-technical systems.
Some evidenced practical experience with machine learning.
An excellent track record of publications in top tier conferences and/or journals in the area of PhD study.
Evidence of programming skills and a good understanding of AI and Machine Learning techniques
Ability to work effectively as part of a team, to meet deadlines, and to report on project progress.
The following desirable criteria will be evaluated by the level of proficiency. Recruitment will aim at selecting those candidates with the best possible performance in these criteria.
Desirable knowledge, skills and experience are:
The PhD and how strongly it focusses on AI, regulation, and autonomous systems
Evidence of willingness/ability to work in an inter-disciplinary research context
Experience in the development of case studies to exemplify particular processes or techniques.
Familiarity with regulation of systems and the processes of standardisation and regulation of systems.
Experience in the study of the embedding of new technical systems in an organisational context.
Experience of research in the broad area of the related project
Preferably, experience in the specific area of the related project
Proven expertise in the techniques needed to undertake the research in question
Demonstrated quality of research performance
Ability to communicate complex information clearly, orally and in writing to both academic and industrial audiences.
Feedback is only provided to interviewed candidates.
Informal enquiries should be directed to Prof Stuart Anderson S.Anderson@ed.ac.uk.
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As a valued member of our team you can expect:
An exciting, positive, creative, challenging and rewarding place to work. We give you support, nurture your talent and reward success. You will benefit from a competitive reward package and a wide range of staff benefits, which includes a generous holiday entitlement, a defined benefits pension scheme, staff discounts, family friendly initiatives , flexible working and much more. Access our staff benefits page for further information and use our reward calculator to find out the total value of pay and benefits provided.
The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. We are members of the Race Equality Charter and we are also Stonewall Scotland Diversity Champions, actively promoting LGBT equality.
If invited for interview you will be required to evidence your right to work in the UK. Further information is available on our right to work webpages.
The University is able to sponsor the employment of international workers in this role. If successful, an international applicant requiring sponsorship to work in the UK will need to satisfy the UK Home Office’s English Language requirements and apply for and secure a Skilled Worker Visa.