About the Role
We seek to appoint four Lecturers or Senior Lecturers in the area of Machine Learning, Social Data Science, Artificial Intelligence and Data Analytics to join our world-class research community. The successful candidates will help to develop our research vision in this exciting new area of strategic growth.
To apply, you should have a PhD or equivalent professional experience and must have an appropriate track-record of high quality research in the relevant fields above. Queen Mary University of London is a signatory of DORA declaration, and as such the quality of your research will be judged on its own merits. This will include, but not be limited to, the value and impact of all your research outputs (including datasets and software) in addition to your research publications, and a broad range of impact measures such as influence on policy and practice.
It is essential that you have clear and ambitious plans for your future research and are able to develop research proposals and effectively manage subsequent awards. It is also essential that you are an effective communicator of new and complex ideas, in both verbal and written form, and that you can engage the interest and enthusiasm of the target audience. You will be passionate about teaching and able and keen to deliver exciting and engaging new courses, at undergraduate and postgraduate level in areas such as, but not exclusively, Databases, Software Engineering, Machine Learning Deployment, Digital Media and Social Networks, Data Analytics and Applied Statistics, Data Mining, Risk and Decision-Making, Artificial Intelligence, and Neural Networks and Deep Learning.
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.
About the School of EECS
As a multidisciplinary School, 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). We welcome staff from diverse backgrounds and our School is keen to reduce the gender gap and provide a positive and flexible working environment for everyone.
We offer competitive salaries, pension scheme, 30 days’ leave per annum, a season ticket loan scheme and access to a comprehensive range of personal and professional development opportunities. In addition, we offer a range of work life balance and family-friendly inclusive employment policies, flexible working arrangements, and campus facilities including an on-site nursery at the Mile End campus.
The posts are based at the Mile End Campus in London and are full time permanent appointments with an expected start date of September 2021. Starting salaries will be in the range of £42,433-£52,833 for Lecturers and £55,840-£62,415 for Senior Lecturers, inclusive of London Allowance. Please note that UK Lecturer and Senior Lecturer positions are equivalent to Assistant Professor and Associate Professor positions respectively in the US.
Queen Mary’s commitment to our diverse and inclusive community is embedded in our appointments processes. We particularly welcome applications from people who identify as Black, Asian or Minority Ethnic groups and for the Senior Lectureship roles women as these groups are underrepresented at this level at Queen Mary. Reasonable adjustments will be made at each stage of the recruitment process for any candidate with a disability. Job share requests for this post will be considered, so please state this clearly on your application.
Informal enquiries should be addressed to Professor Steve Uhlig at email@example.com. Details about the School can be found at www.eecs.qmul.ac.uk.
Candidates are advised that reference letters, certificates and/or research papers, should not be submitted at this stage.
To apply for the role, please click the ‘apply’ button below.
The closing date for applications is 15 August 2021. Interviews are expected to be held in late August/ early September 2021.