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Position: Postdoc in Quantitative Social Sciences/Social Data Science
Institution: University of Luxembourg
Location: Luxembourg City, Luxembourg
Duties: Contribute to the project’s research on cognitive aging and dementia. Use recent machine learning approaches in combination with causal inference tools for observational data. Conduct and prepare statistical analyses for publication in leading international peer-reviewed journals. Disseminate findings at conferences and meetings
Requirements: Strong methodological background (data science, machine learning). Strong programming skills (expert knowledge in R or Python). Fluency in English language. PhD with strong methodology/statistics training, in combination with some higher education in Social Sciences, Population Health, Epidemiology, or related fields. Prior experience with causal inference frameworks will be considered an asset. Strong ability to work both independently and as part of a team
   
Text: UOL02605 31-Jan-2019 Company Text Postdoc (m/f) in Quantitative Social Sciences/Social Data Science The University of Luxembourg (UL) invites applications for a Postdoc position (m/f) at the Institute for Research on Socio-Economic Inequality. Two-year fixed-term contract, renewable to up to three additional years, full-time (40h/week) Ref. 50013954 Framework: The postdoc will contribute to the success of the project ‘Cognitive Aging: From Educational Opportunities to Individual Risk Profiles’ funded by the European Research Council (2019-2023). Project framework: Cognitive impairment and dementia have dramatic individual and social consequences, and create high economic costs for societies. At the moment, no large-scale low-cost risk scores are available that can reliably predict cognitive evolution on an individual level. The project will quantify the ability of singular and clustered individual characteristics, such as indicators of behaviour change, to predict cognitive aging and diagnosis of dementia. The successful candidate will apply non-parametric supervised machine learning approaches on different large-scale individual-level longitudinal data of international aging surveys, in order to identify risk profiles that are predictive of cognitive decline and/or dementia. The project will take into account causal inference frameworks, applicable to observational studies, recently developed in computer sciences and epidemiology. Identifying the value of behaviour change to delay cognitive impairment will guide treatment plans for individuals affected by dementia. Your Role Contribute to the project’s research on cognitive aging and dementia Use recent machine learning approaches in combination with causal inference tools for observational data Conduct and prepare statistical analyses for publication in leading international peer-reviewed journals Disseminate findings at conferences and meetings Please contact Anja Leist (anja.leist@uni.lu) in case of further questions. Your Profile Strong methodological background (data science, machine learning) Strong programming skills (expert knowledge in R or Python) Fluency in English language PhD with strong methodology/statistics training, in combination with some higher education in Social Sciences, Population Health, Epidemiology, or related fields Prior experience with causal inference frameworks will be considered an asset Strong ability to work both independently and as part of a team We offer A position in a highly visible research project at the frontiers of knowledge in the field of social sciences and dementia Opportunities for further training, international mobility, networking Opportunities to contribute to and collaborate with members of the ‘computational and data science’ research priority across faculties/centres at UL A multi-disciplinary, international, well-equipped work environment Gender policy: UL is an equal opportunity employer. Women are explicitly encouraged to apply. Further Information All applications need to be sent through the online submission system via link below. Please upload the following documents in PDF format: Curriculum Vitae with list of publications Motivation letter (1-max. 2 pages) detailing your interest to contribute to the CRISP project Contact details of two persons with full name and institution that can be approached as referees Copies of diplomas or transcripts with grades if issued in a language other than English, French or German Deadline for applications is 31 January 2019. Shortlisted applicants will be invited for an interview on site or via video conference call. The ERC StG project CRISP (grant no. 803239, PI: Assoc. Prof. Anja Leist ) ‘Cognitive Aging: From Educational Opportunities to Individual Risk Profiles’ is an interdisciplinary project located in the Social Sciences. Find out more about the host institute and the project . For candidates applying from outside the EU, please consult the Foreign Researcher’s Guide to Luxembourg .
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