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Advanced Quantitative ResearchStatistical AnalysisRLarge-Scale Data AnalysisData Linkage
Requirements
Applicants should have a PhD in Human Resource Management, Employment Relations, Sociology of Work and Employment, Labour Economics, or a related discipline, along with advanced quantitative research skills and high-level research methods training. They should have experience with large, nationally representative datasets, data linkage, and statistical packages such as R, a strong record of high-quality publications, and knowledge of research on the digital transformation of work.
Job Description
Do you have a PhD in Human Resource Management, Employment Relations, Sociology of Work and Employment, Labour Economics or related disciplines? Do you have experience of working with large, nationally representative data sets, data-linkage and relevant statistical packages such as R?.
You will have demonstrable evidence of high-level research methods training, and, for this post specifically, advanced quantitative research skills. You will be expected to have evidence of published work of high quality, and a strong knowledge of relevant conceptual and empirical literatures relating to the digital transformation of work. Applicants with background understanding and prior research expertise of the changing nature of work and digital transformation are particularly encouraged, as are applicants with expertise in comparative study. Applicants should be willing to work on a variety of research projects and to travel, when required, for national and international meetings and dissemination and engagement activities.
Leeds University Business School is looking to recruit a Quantitative Research Fellow for the ESRC Centre for Digital Futures at Work (DIGIT). Digit is jointly directed by the Universities of Leeds and Sussex, in collaboration with the Universities of Manchester, Cambridge and Monash. Digit was established in 2020 and is now on its second phase research programme (2025-2029), supported by an ESRC Grant of £8.2 million. Digit brings together an interdisciplinary, international network that aims to advance understanding of how digital technologies are reshaping work, impacting on employers, employees, job seekers and governments. The centre’s core research programme is focused on digital ecosystems, and includes five research themes that investigate: fragmented digital governance; digital adoption; skills and reward, wellbeing; location and environment. Two further waves of Digit’s unique Employers’ Digital Practices at Work survey are planned.
The Quantitative Research Fellow will work on the Digital Practices at Work Survey (DPAW), and other secondary and administrative data sets, in collaboration with Digit co-Director Professor Mark Stuart and Professor Danat Valizade, and other members of the research team. It is anticipated that the Fellow will focus on a number of projects related to analysis of DPAW and the linking of DPAW with other large-scale nationally representative datasets, such as Understanding Society, and comparator studies conducted in other countries. Topics for investigation will include: the changing trends in the adoption of digital technologies and AI on work-related issues, such as skills, rewards, work organisation and employee well-being; the impact of AI on jobs at a regional level; different trends in the nature of AI adoption by technology type between countries. There will be plenty of scope for the Fellow to help define and shape the focus on ongoing research.
Salary Requirements of the Skilled Worker Visa Route
G7 - Please note that this post may be suitable for sponsorship under the Skilled Worker visa route but first-time applicants might need to qualify for salary concessions. For more information please visit: www.gov.uk/skilled-worker-visa.
For research and academic posts, we will consider eligibility under the Global Talent visa. For more information please visit: https://www.gov.uk/global-talent
To explore the post further or for any queries you may have, please contact:
Professor Mark Stuart - Co-Director: ESRC Digital Futures at Work Research Centre
Email: M.A.Stuart@lubs.leeds.ac.uk
Or
Prof Danat Valizade - Professor of Quantitative Employment Research
Email: D.Valizade@leeds.ac.uk
Information for disabled candidates
Information for disabled candidates, impairments or health conditions, including requesting alternative formats, can be found on our Accessibility information page or by getting in touch with us at hr@leeds.ac.uk
You will have demonstrable evidence of high-level research methods training, and, for this post specifically, advanced quantitative research skills. You will be expected to have evidence of published work of high quality, and a strong knowledge of relevant conceptual and empirical literatures relating to the digital transformation of work. Applicants with background understanding and prior research expertise of the changing nature of work and digital transformation are particularly encouraged, as are applicants with expertise in comparative study. Applicants should be willing to work on a variety of research projects and to travel, when required, for national and international meetings and dissemination and engagement activities.
Leeds University Business School is looking to recruit a Quantitative Research Fellow for the ESRC Centre for Digital Futures at Work (DIGIT). Digit is jointly directed by the Universities of Leeds and Sussex, in collaboration with the Universities of Manchester, Cambridge and Monash. Digit was established in 2020 and is now on its second phase research programme (2025-2029), supported by an ESRC Grant of £8.2 million. Digit brings together an interdisciplinary, international network that aims to advance understanding of how digital technologies are reshaping work, impacting on employers, employees, job seekers and governments. The centre’s core research programme is focused on digital ecosystems, and includes five research themes that investigate: fragmented digital governance; digital adoption; skills and reward, wellbeing; location and environment. Two further waves of Digit’s unique Employers’ Digital Practices at Work survey are planned.
The Quantitative Research Fellow will work on the Digital Practices at Work Survey (DPAW), and other secondary and administrative data sets, in collaboration with Digit co-Director Professor Mark Stuart and Professor Danat Valizade, and other members of the research team. It is anticipated that the Fellow will focus on a number of projects related to analysis of DPAW and the linking of DPAW with other large-scale nationally representative datasets, such as Understanding Society, and comparator studies conducted in other countries. Topics for investigation will include: the changing trends in the adoption of digital technologies and AI on work-related issues, such as skills, rewards, work organisation and employee well-being; the impact of AI on jobs at a regional level; different trends in the nature of AI adoption by technology type between countries. There will be plenty of scope for the Fellow to help define and shape the focus on ongoing research.
Salary Requirements of the Skilled Worker Visa Route
G7 - Please note that this post may be suitable for sponsorship under the Skilled Worker visa route but first-time applicants might need to qualify for salary concessions. For more information please visit: www.gov.uk/skilled-worker-visa.
For research and academic posts, we will consider eligibility under the Global Talent visa. For more information please visit: https://www.gov.uk/global-talent
To explore the post further or for any queries you may have, please contact:
Professor Mark Stuart - Co-Director: ESRC Digital Futures at Work Research Centre
Email: M.A.Stuart@lubs.leeds.ac.uk
Or
Prof Danat Valizade - Professor of Quantitative Employment Research
Email: D.Valizade@leeds.ac.uk
Information for disabled candidates
Information for disabled candidates, impairments or health conditions, including requesting alternative formats, can be found on our Accessibility information page or by getting in touch with us at hr@leeds.ac.uk
Education
Postgraduate Degree
Skills
Advanced Quantitative ResearchStatistical AnalysisRLarge-Scale Data AnalysisData LinkageAdministrative Data AnalysisSurvey ResearchComparative ResearchResearch MethodsAcademic PublishingDigital Transformation ResearchEmployment ResearchInterdisciplinary CollaborationResearch Project Development