Quantitative Research Fellow, Digital Futures at Work

Leeds; Leeds; On-site; GBP 65,000 - 75,000; Full time

Job summary

Leeds University Business School seeks a Quantitative Research Fellow for the ESRC Centre for Digital Futures at Work (DIGIT). The role focuses on analysing the Digital Practices at Work Survey (DPAW) and linking it with large-scale datasets, collaborating with DIGIT co-Director Professor Mark Stuart and Professor Danat Valizade.

Applicants should have a PhD and high-level quantitative skills, experience with data linkage and statistical software such as R, and a strong record of published work

Qualifications

• PhD in Human Resource Management, Employment Relations, Sociology of Work and Employment, Labour Economics or related disciplines.
• Experience of working with large, nationally representative data sets, data-linkage and statistical packages such as R.
• Evidence of published work of high quality and knowledge of relevant conceptual and empirical literatures relating to the digital transformation of work.
• Willingness to travel for national and international meetings and dissemination and engagement activities.

Responsibilities

• Work on the Digital Practices at Work Survey (DPAW) and other secondary and administrative data sets in collaboration with the DIGIT team.
• Link DPAW with other large-scale nationally representative datasets, such as Understanding Society.
• Help define and shape the focus on ongoing research within DIGIT and related projects.
• Explore topics on AI adoption and its impact on work at regional and country levels.

Skills

Advanced quantitative research skills

Education

PhD in Human Resource Management, Employment Relations, Sociology of Work and Employment, Labour Economics or related disciplines

Tools

R

Job description

Leeds University Business School seeks a Quantitative Research Fellow for the ESRC Centre for Digital Futures at Work (DIGIT). The role focuses on analysing the Digital Practices at Work Survey (DPAW) and linking it with large-scale datasets, collaborating with DIGIT co-Director Professor Mark Stuart and Professor Danat Valizade.

Applicants should have a PhD and high-level quantitative skills, experience with data linkage and statistical software such as R, and a strong record of published work