Reader in Artificial Intelligence

4 weeks ago


Wolverhampton, United Kingdom University of Wolverhampton Full time

Artificial Intelligence is a strategic growth area for University of Wolverhampton, and we are seeking to appoint an exceptional and ambitious individual to join our team as a Reader in Artificial Intelligence.

Artificial Intelligence is a strategic growth area for University of Wolverhampton, and we are seeking to appoint an exceptional and ambitious individual to join our team as a Reader in Artificial Intelligence. The School of Engineering, Computing and Mathematical Sciences is a large interdisciplinary centre for education, research, and enterprise. We are looking for an experienced researcher to help lead, drive, and advance our research and knowledge exchange activities in Artificial Intelligence.

The School of Engineering, Computing and Mathematical Sciences operates at Wolverhampton City campus, Telford Innovation Campus, Wolverhampton Science Park, Springfield (Elite Centre for Manufacturing Skills (ECMS)) and Hereford (Cyber Quarter). The school’s portfolio also includes UWRacing, Cyber Quarter (Hereford) and the IoT Dudley. The School provides education, business engagement, and research, and supports many companies focusing on advanced engineering, motorsport engineering, computer science, artificial intelligence and cyber security. The portfolio includes a diverse range of contemporary undergraduate and postgraduate accredited programmes, including a growing transnational provision, degree apprenticeships, and online courses.

The Department of Computing and Mathematical Sciences offers a full range of contemporary, professionally accredited programmes incorporating Foundation Year, Undergraduate, Taught Postgraduate, Transnational Education as well as Degree Apprenticeships and Doctoral level study opportunities. These include key areas such as Computer Science, Cyber Security, Information Technology and Mathematics, as well as emerging fields such as Artificial Intelligence and Data Science.

You should have evidence of an individual track record in research which is at the cutting edge of the relevant fields and is recognised internationally (e.g., through publications in journals). You should have a track record of having successfully obtained funding from external sources and successfully completed projects.

**The University of Opportunity for Students and Staff



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