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The University of Manchester seeks a full-time Research Associate for the ESRC funded project 'Survey Futures'. This role involves methodological research, leadership and engagement activities aimed at enhancing the quality and effectiveness of social surveys in the UK, alongside a collaborative team from various organizations.
Applications are sought for a talented and ambitious full-time Research Associate to carry out methodological research, leadership, management and engagement activities for the ESRC funded project: SDCMC: Survey Data Collection Methods Collaboration: Securing the Future of Social Surveys, to be known as Survey Futures.
Survey Futures is a collaboration between nine universities and three survey organisations, in partnership with the National Centre for Research Methods (NCRM) and the Office for National Statistics (ONS). Its objective is to deliver a step-change in survey research to ensure that it will remain possible in the UK to carry out high-quality social surveys of the kinds required by the public and academic sectors. The post is based in the Social Statistics Department, School of Social Sciences, University of Manchester, and will involve working on methodological research and theoretical development for Survey Futures, together with the University of Manchester investigators, Dr Alexandru Cernat and Professor Natalie Shlomo, in collaboration with partners across participating organisations. The Director is Professor Peter Lynn of ISER, the University of Essex and the Deputy Director is Dr Olga Maslovskaya, University of Southampton. The appointment will be funded for 9 months.
Survey Futures aims to assess the quality implications of the most important survey design choices relevant to future UK social surveys, to provide good practice guidance and practical training materials, and to identify promising ways to improve the capacity and skillset of both interviewers and research professionals.
This post will mainly contribute to one of the Survey Futures research strands: "Research Strand 7: Data integration" and to training and capacity building and other activities of the collaboration.
The post requires an understanding of survey methods and statistics, and a commitment to rigorous evaluation and to effective dissemination.
What you will get in return: