Lecturer/Senior Lecturer in Data Analytics
1 day left
- Full Time
Department: School of Electronic Engineering & Computer Science
Salary: £41,682-£51,899; for Senior Lecturer it will be in the range of £54,853-£61,311 per annum (Grade 7)
Location: Mile End
Closing date: 18-Jul-2019
The School of Electronic Engineering and Computer Science (EECS) is an exciting and dynamic environment with a reputation for excellence in both research and teaching. As a multidisciplinary School, our researchers work with the arts and sciences collaborating with psychologists, biologists, musicians and actors, mathematicians, medical researchers, dentists and lawyers. We are well known for our pioneering research and pride ourselves on our world-class projects. We are 11th in the UK for quality of computer science research (REF 2014) and 6th in the UK for quality of electronic engineering research (REF 2014). Our academics undertake world-leading research in a lively and supportive research community. The results are original, informative, often surprising or questioning, and always significant, achieving impact on wider society and within specialist areas of knowledge.
We are currently looking to appoint four Lecturers or Senior Lecturers in Data Analytics who will provide teaching and ongoing research within one or more of our current research groups and centres (http://eecs.qmul.ac.uk/research/research-groups/).
To apply, you should have a PhD in Electronic Engineering, Computer Science, or equivalent professional experience, and have a track-record of high quality research in the field of Data Analytics at a national, and ideally international, level including publications in renowned journals. You should have clear and ambitious plans for your future research and be able to develop research proposals, bid for and secure external research funding, and effectively manage subsequent awards.
Your experience must cover teaching at undergraduate and/or postgraduate level in large or small group settings and you should be experienced in least two of the following areas as you will be expected to assume a standard academic teaching workload in these subjects: Data Mining; Big Data Processing; Bayesian Decision and Risk Analysis; Advanced Data Modelling; Applied Statistics; Cloud Computing.
A successful applicant at Lecturer level will have some experience of teaching and, with some guidance, will be able to deliver teaching at both undergraduate and postgraduate levels. It is expected that your research is at an appropriate level for your career stage.
At Senior Lecturer level, successful applicants will have a proven research track record and will be able to deliver teaching and assessment with limited guidance. You will also have a record of mentoring and developing staff, including successful supervision of PhD students to completion.
These posts are full time and permanent and each post holder will ideally be in position by 1 September 2019, but must be able to start no later than 1 January 2020 due to teaching constraints. For an appointment at Lecturer level, the starting salary will be in the range of £41,682-£51,899; for Senior Lecturer it will be in the range of £54,853-£61,311. Benefits include 30 days’ annual leave, pension scheme and an interest-free season ticket loan.
At Queen Mary University of London, we are committed to the equality of opportunities and to advancing the careers of all staff. We have policies to support staff returning from long-term absence and flexible arrangements for staff to who wish to change their work patterns. As part of our commitment to the Athena SWAN principles we strongly encourage applications from women.
Candidates must be able to demonstrate their eligibility to work in the UK in accordance with the Immigration, Asylum and Nationality Act 2006. Where required this may include entry clearance or continued leave to remain under the Points Based Immigration Scheme. The School will be able to provide a Certificate of Sponsorship if required by the successful candidate.
To apply, please click on the apply link below
Please include your H-index score and the link to your Google Scholar page in your CV. However, reference letters, certificates and/or large documents, should not be submitted with your application.
The closing date for applications is 18th July 2019.
Interviews will be held in late August.
Valuing Diversity & Committed to Equality
QMUL is proud to be a Living Wage employer