Share
Institution: University of Bath
United Kingdom
Retrieved : 2018-10-05 Expired
Description :

The Department of Computer Science at the University of Bath wishes to appoint an academic with internationally leading expertise in machine learning and data science. This appointment is part of a strategic drive to strengthen and integrate our core research themes. Key strengths include probabilistic machine learning, data science, artificial intelligence, computer vision, image and video analysis. The post holder will be expected to extend our core strengths and to create effective collaborations with colleagues across the Department’s research groups: Intelligent Systems, Visual Computing, Human-Computer Interaction and Mathematical Foundations.

Across the University, there are exciting opportunities for interdisciplinary research and teaching collaborations. For example, the Department of Computer Science collaborates with the Bath Institute for Mathematical Innovation and the Department of Mathematical Sciences on our MSc Data Science. We also work closely with the Department of Electronic & Electrical Engineering on our new MSc Machine Learning & Autonomous Systems.

In research, the Department of Computer Science collaborates with the Department for Health in CAMERA, the Centre for the Analysis of Motion, Entertainment Research and Applications. Other opportunities for interdisciplinary collaboration include the Bath Astrophysics Group, e.g. supporting the new Square Kilometer Array; the Institute for Policy Research with direct links to policy advice for Government, e.g. the “datafication and democracy” project; and the Milner Centre for Evolution, e.g. applications of machine learning to gene regulatory networks.

Beyond the University, the post holder is expected to engage with and expand the list of national and international collaborators in both academia and industry. External collaborators include UCL, Cardiff, Oxford, Cambridge, Tsinghua, Zhejiang, São Paulo, the Office for National Statistics, the NHS, BBC and many others.

Applicants will be expected to hold a PhD and to have an international reputation for excellent publications, backed up by an excellent track record and outstanding potential to lead research, funding bids and teaching. The post holder will contribute to teaching and must have a continuing commitment to maintaining the University’s high standards in teaching and learning, with the ability to educate and inspire some of the brightest students in the country. The post holder is likely to support in particular the MSc Data Science and MSc Machine Learning & Autonomous Systems. Topics include the theory and practice of data science and specialisation in probabilistic machine learning, statistics and related software technologies. The successful applicant will be expected to carry out and supervise research in line with targets set by the Department and to obtain significant research funding from external sources. The post holder will also be expected to contribute to the administration, leadership and management of the Department’s activities commensurate with the level of the appointment.

The Department and the University are committed to providing a supportive and inclusive working environment. We are working to improve the gender balance within the Department and particularly welcome applications from women.

For an informal discussion about the roles, please contact Prof Eamonn O’Neill (E.ONeill@bath.ac.uk or +44 (0)1225 383216).

Please Note:
This is a “rolling advert” with a nominal closing date only. Applications are welcome at any time and the timing of the selection process will be dependent on the applications received.

The first round of shortlisting is scheduled for 25 October 2018.

Closing Date: 04 Nov 2018
Type: Education & Research





Disclaimer : We aim to provide correct and reliable information about upcoming events, but cannot accept responsibility for the text of announcements or for the bona fides of event organizers. Please feel free to contact us if you notice incorrect or misleading information and we will attempt to correct it.