Tenure-Track Professor/Associate Professor/Assistant Professor in Quantitative Methods in the Social Sciences (several posts)

Applications are invited for Tenure-Track Professor/Associate Professor/Assistant Professor in Quantitative Methods in the Social Sciences (several posts) in the Faculty of Social Sciences (Ref.: 522397), to commence as soon as possible, on a three-year fixed-term basis with the possibility of renewal and consideration for tenure before the expiry of a second three-year fixed-term contract.  Exceptionally outstanding candidates at Professor/Associate Professor level may be considered for appointment on direct tenure terms subject to University’s approval. 

The University of Hong Kong Faculty of Social Sciences

Founded in 1911, the University of Hong Kong is committed to the highest international standards of excellence in teaching and research, and has been at the global forefront of academic scholarship for many years.  The Faculty of Social Sciences was established in 1967 and consists of six Departments.  Underpinning the Departments are Faculty’s strategic research clusters and commitments in diverse research methodologies, which represents the areas of strength in which the Faculty is investing further resources to elevate the scale and impact of our research. 

Position Description

The Faculty of Social Sciences seeks senior leaders to help us achieve our ambition of being at the forefront of methodological innovation in the Social Sciences in research and teaching. We have developed the Methods Hub within the Social Sciences Research Centre at the Faculty to strengthen our quantitative method expertise in research and teaching. The aim of the Social Sciences Research Centre is to substantially enhance our methodological expertise in the Social Sciences, and to raise the quality and coherence of research methods training for students and staff. We are now recruiting open-rank tenure-line faculty members in the field of Computational Social Sciences with an outstanding quantitative research programme in the Social Sciences. 

The successful applicants will help build quantitative infrastructure across the Faculty, and oversee upskilling of expertise in our staff and students. The appointees will have teaching responsibilities in the area of quantitative methods for the Social Sciences, and be expected to continue their high-impact research programme. The appointees will be housed within one of our departments, working with the Social Sciences Research Centre across the Faculty. 

Applicants should possess a track record of high impact publications and a sustained record of success at obtaining large-scale competitive research funding on the topic of methodological innovation in the social sciences. Experience in raising philanthropic funds will be an advantage, as well as the demonstrated ability to create real-world impact through their research agenda. Applicants who are aligned with the academic disciplines represented by the departments within the Faculty of Social Sciences, and who are able to reach out to colleagues across the disciplines in our Faculty and University are preferred. 

Essential Criteria

• A PhD in one of the Quantitative Social Sciences or Computational Social Sciences;
• Distinguished achievement of excellence in research as evidenced by high quality track-record of international publications on methodological innovation in quantitative/computational social sciences;
• A track record of research grant income on the topic of methodological innovation in quantitative/computational social sciences;
• A track record of having led research grants;
• A track record of conducting social sciences research that impacts on policy and practice.
• Evidence of successful academic leadership and management;
• Demonstrable evidence of high-quality teaching: innovative approaches to teaching, supervising or assessment; and the use a range of delivery techniques to enthuse and engage students;
• Experience of teaching excellence in Computational Social Sciences;
• Experience of using a virtual learning environment to deliver teaching;
• Significant experience in the planning and delivery of new undergraduate and taught postgraduate courses and programmes;
• Proven experience of successfully supervising doctoral students.

Desirable

• Experience of developing or leading teaching programmes related to Computational Social Sciences;
• Teaching experience in courses related to Machine Learning, Big Data, Data Mining, Simulation, Data Visualisation and Natural Language Processing;
• A strong track record of establishing links with relevant academic and non-academic institutions. 

A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits.  At current rates, salaries tax does not exceed 15% of gross income.  The appointment will attract a contract-end gratuity and University contribution to a retirement benefits scheme, totalling up to 15% of basic salary. Housing benefits will be provided as applicable. 

How to Apply

The University only accepts online application for the above posts.  Applicants should apply online and upload (1) an up-to-date CV with contact information of three referees, (2) a cover letter, (3) a research plan, and (4) a statement on teaching philosophy.  Applications should consist of a cover letter together with an up-to-date CV and related dossier.  Review of applications will start as soon as possible and continue until July 25, 2023, or until the posts are filled, whichever is earlier.