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Position: Associate Lecturer (Teaching) in Statistics
Institution: University College London
Department: Research Department of Epidemiology & Public Health
Location: London, United Kingdom
Duties: The two posts will be within the join Rigorous Training in Longitudinal Data Science (RADIANCE) project. One part-time post (70% FTE) will be based at the Research Department of Epidemiology and Public Health reporting to Professor Paola Zaninotto. The other full-time post (100% FTE - part-time and job share will be considered) will be based at the Institute of Child Health, Population, Policy and Practice Programme reporting to Professor Bianca De Stavola and Dr Pia Hardelid. The aim is to develop and deliver a comprehensive, cohesive and rigorous training package aimed at the broad community of quantitative researchers involved in the management, analysis and interpretation of longitudinal biosocial data and the production of rigorous and transparent scientific evidence
Requirements: Degree in statistics (MSc or PhD) or equivalent level of attainment or equivalent experience; Essential skills: experience of teaching/training in statistics; Desirable skills: experience of working in a multi-disciplinary team in a research or academic setting. Experience of a range of teaching methods, including lectures, small group teaching, individual supervision, tutorials and computer-assisted learning
   
Text: Associate Lecturer (Teaching) in Statistics, - Ref:1879835 Click here to go back to search results Apply Now UCL Department / Division Research Department of Epidemiology & Public Health Location of position London Grade 7 Hours Part Time Hours per week (%FTE) 25.55 hours per week (70% FTE) Salary (inclusive of London allowance) £40,928 per annum Salary pro-rata for part time vacancies Duties and Responsibilities The two posts will be within the join Rigorous Training in Longitudinal Data Science (RADIANCE) project. One part-time post (70% FTE) will be based at the Research Department of Epidemiology and Public Health reporting to Professor Paola Zaninotto. The other full-time post (100% FTE - part-time and job share will be considered) will be based at the Institute of Child Health, Population, Policy and Practice Programme reporting to Professor Bianca De Stavola and Dr Pia Hardelid. The aim is to develop and deliver a comprehensive, cohesive and rigorous training package aimed at the broad community of quantitative researchers involved in the management, analysis and interpretation of longitudinal biosocial data and the production of rigorous and transparent scientific evidence. The project is funded by UKRI and is available until 31/08/2023 in the first instance. Key Requirements Degree in statistics (MSc or PhD) or equivalent level of attainment or equivalent experience. Essential skills: experience of teaching/training in statistics. Desirable skills: experience of working in a multi-disciplinary team in a research or academic setting. Experience of a range of teaching methods, including lectures, small group teaching, individual supervision, tutorials and computer-assisted learning. Further Details A job description and person specification can be accessed via the link at the bottom of this page. To apply for the vacancy please click on the Apply Now button below. Informal enquiries can be made to: Dr Paola Zaninotto (p.zaninotto@ucl.ac.uk). If you have any queries regarding the application process please contact Floriana Bortolotti (f.bortolotti@ucl.ac.uk). UCL Taking Action for Equality We will consider applications to work on a part-time, flexible and job share basis wherever possible. Closing Date 6 Feb 2022 Latest time for the submission of applications 23:59 Interview date 11th February 2022 Our department holds an Athena SWAN Silver award, in recognition of our commitment and demonstrable impact in advancing gender equality. This appointment is subject to UCL Terms and Conditions of Service for Research and Support Staff. Please use these links to find out more about UCL working life including the benefits we offer and UCL Terms and Conditions related to this job. ICH Job description EPH Job description Apply Now
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