The Social Statistics Department is seeking to appoint a Lecturer / Senior Lecturer in Social Statistics. Applicants must have established an international reputation in Social Statistics, supported by a strong record of published research output and a wider record of achievement. Applicants with specializations across Quantitative Social Science are invited, but specializations and approaches that build on strengths of the Department of Social Statistics are particularly welcome. This includesmethodological research on survey statistics, small area estimation, statistical analysis of complex surveys, longitudinal, administrative and other forms of data, statistical disclosure control, causal inference. Substantive research interests of applicants can include, but are not limited to,social inequalities, health and well-being, and demography. Commensurate with experience, applicants should also have a clear and viable strategy for applying for external research funding, as and where appropriate.
The department of Social Statistics is part of the School of Social Sciences. It was launched in January 2009 with the aim of improving the methodological rigour and range of quantitative enquiries in social science. Social statistics covers statistics of all aspects of society, and statistical methods that are applicable within the field of social enquiry. The Social Statistics Department encourages innovations in quantitative methodology, the application of cutting-edge statistical methods in social contexts, and the analysis of complexities in social data. Our research activity is both methodological and substantive, for example, with interests in both traditional as well as new and emerging methods, health and social inequalities, population dynamics, new forms of data and computational social sciences.
Our strapline ‘making a differencewith data’ has helped increase our intake on teaching programmes, such as BA Economics and Data Analytics, BA Social Science and Data Analytics, MSc Social Research Methods and Statistics, MSc Data Science (Social Analytics pathway). The University of Manchester’s Q-Step Centre, which is led by the Department of Social Statistics, is sector leading. Through Q-Step our undergraduates develop their data and statistical skills and have the opportunity to undertake a data fellowship (paid work placement) as part fo their degree. Our methodological research with survey, census, longitudinal, multilevel and new forms of data informs our interdisciplinary research applications in topics such as employment, ageing, health, inequalities, and migration. In addition, our research into survey statistics and methods, statistical modelling, small area estimation, privacy and confidentiality, missing data problems, demography, social network analysis and computational social sciences has made Social Statistics into one of the leading departments in the country. Our research strengths are reflected in our top rating as part of the Sociology submission for the 2014 and 2021 REF.
Applications should be made on line and include:
a) A cover letter setting out how you meet the selection criteria (Person specification)
b) A curriculum vitae (CV) that includes any publications. Applicants are also asked to indicate two most significant publications or other appropriate outputs.
What you will get in return:
- Fantastic market leading Pension scheme
- Excellent employee health and wellbeing services including an Employee Assistance Programme
- Exceptional starting annual leave entitlement, plus bank holidays
- Additional paid closure over the Christmas period
- Local and national discounts at a range of major retailers
As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.
Our University is positive about flexible working you can find out morehere
Hybrid working arrangements may be considered.
Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.
Any recruitment enquiries from recruitment agencies should be directed to .
Any CV’s submitted by a recruitment agency will be considered a gift.
Enquiries about the vacancy, shortlisting and interviews:
Prof Arkadiusz Winiowski (Head of Department)
Email:
Tel: +44(0)161-275-4738
General enquiries:
Email:
Technical support:
https://jobseekersupport.jobtrain.co.uk/support/home
This vacancy will close for applications at midnight on the closing date.
Please see the link below for the Further Particulars document which contains the person specification criteria.
