Lecturer or Reader in Computational Social Science

Open ended contract - Permanent: Full-time - 35 hours per week.

Applications are invited for a Lecturer/Reader position (comparable to Assistant/Associate Professor) in Computational Social Science in the School of Informatics.

Computational Social Science uses methods from informatics and computer science to study social attitudes, behaviour, or other social phenomena. Candidates with interest in big social data analysis, graph/web mining, web science, or natural language processing applications for social science are particularly encouraged to apply.

The successful candidate will have (or be near to completing) a PhD in a relevant area, an established research agenda, demonstrated via an excellent publications record, the enthusiasm and ability to undertake original research, and to lead a research group. They will show excellent teaching capability and engagement with academic supervision.

For exceptional applicants, appointments may be available as a Reader (Grade UE09).

All applications must contain the following supporting documents:

Teaching statement (1-2 pages)
Research statement (2-3 pages)

Full CV and publication list, which should identify applicant’s 3 most relevant/representative publications

Further Information

We seek candidates with an interdisciplinary research profile in computational social science. They are expected to have a strong track-record of publications in leading conferences in computational social science.

Candidates should be comfortable contributing to core teaching in computer science and AI, as well as delivering more specialized topics. The successful candidate would be expected to develop a new course in computational social science that teaches the main foundations in this field.

The successful candidate would be expected to contribute to the expansion of the existing work on computational social science at the school by bringing funded projects and recruiting grad students and post-doctoral researchers to cover novel research directions in the field.

Your skills and attributes for success:

UE08 Lecturer:

PhD and experience as an established academic in computational social science or a related field (e.g. HCI, NLP, and data science in general).

Candidates who are close to completing their PhD (ie. thesis submission is imminent), and who otherwise meet the selection criteria, will be considered.

Ability to undertake original research, including leading a research group.

Ability to attract research funding as an independent researcher.

A track record of first author and/or collaborative publications in high quality journals and international conferences.

Strong relevant research and teaching skills.

Effective written and oral communication skills in a range of contexts (e.g. teaching, research presentations and publications).

Ability to contribute to teaching on a range of non-Honours courses as well as in more specialist areas of machine learning.

The ability to engage with a range of teaching mediums including online and distance learning.

UE09 Reader*: as above and including:

Proven ability to provide leadership for activities in delivering the School’s objectives.

Extensive experience in research, postgraduate supervision and teaching.

Proven ability to foster and embed a strong student-focused culture.

Evidence of significant achievement in the relevant field through (e.g.) successful knowledge transfer from research to academic community, public, private and/or voluntary sectors and general public; the receipt of prestigious prizes and awards; membership of national and international bodies relevant to the research field.

Experience of managing, motivating and developing research staff, students and projects

.*PhD must be completed for a Reader appointment.

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