|Title: Lecturer (Assistant Professor); Senior Lecturer/Reader (Associate Professor) in Data Science and Machine Learning||Posted: February 18, 2017|
|Company/Institution: University of Bath|
|Location: Bath, UK|
|Department: Computer Science|
Description: Salary: Starting from £39,324, rising to £46,924 (Lecturer) or £48,327, rising to £55,998 (Senior Lecturer/Reader)
Interview Date: To be confirmed
Start of post: August-September 2017
The Department of Computer Science at the University of Bath is seeking academics with internationally leading expertise in Data Science and Machine Learning. Candidates must have an excellent track record and outstanding potential to lead research, funding bids and teaching. We wish to appoint two people at Lecturer (Assistant Professor) or Senior Lecturer/Reader (Associate Professor) level, with corresponding salary range, as appropriate to the successful candidates.
These appointments are part of a strategic drive to strengthen and integrate our core research themes. Key strengths include data science, machine learning, probabilistic modelling, artificial intelligence, computer vision, image and video analysis. The post holders 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. In particular, the Bath Institute for Mathematical Innovation [www.bath.ac.uk/imi] supports a range of industrial engagements via researchers, secondments and funding. Other examples include the Bath Astrophysics Group [www.bath.ac.uk/physics/research/astrophysics], e.g. supporting the new Square Kilometer Array; the Institute for Policy Research [www.bath.ac.uk/ipr] with direct links to policy advice for Government, e.g. the “datafication and democracy” project; and the Milner Centre for Evolution [www.bath.ac.uk/groups/milner-centre-for-evolution], e.g. applications of machine learning to gene regulatory networks.
Beyond the University, the post holders are 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, The Imaginarium, BBC, Disney and many others.
The post holders 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. In particular, the post holders will support the strategic launch of a new MSc in Data Science. Topics include the theory and practice of data science and specialisation in machine learning, statistics and related software technologies.
Applicants will normally be expected to hold a PhD and to have an international reputation for excellent publications, backed up by appropriate research funding and activity. The successful applicants 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 holders 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.
Application Instructions: For informal discussion about the roles, please contact Prof Eamonn O’Neill, [E.ONeill@bath.ac.uk], +44 (0)1225 383216 or Prof Mike Tipping, [M.Tipping@bath.ac.uk], +44 (0)1225 386964.
Further details can be found at the application portal.
The University of Bath is an equal opportunities employer and has an excellent international reputation with staff from over 60 different nations. To achieve our global aspirations, we welcome applicants from all backgrounds.