Post-doc position in Statistics/Machine Learning in Paris, France
We are looking for a postdoc candidate for the project of “A high dimensional statistical approach to study health and aging”, who will successfully apply to the MSCA Postdoctoral Fellowship 2022 call.
Offer deadline: 15 June 2022 5PM Europe/Brussels time
EU Research framework programme:: HE/MSCA Postdoctoral Fellowship
Location: France, Paris, Ile de France [Cergy, La Défense]
Host organization: ESSEC Business School
KEYWORDS: (high dimensional) statistics and probability, machine learning, longitudinal data analysis, functional data analysis, aging, health, risk factors
RESEARCH INTERESTS of the candidate
• Interests in developing advanced statistical methodology for solving real problems
• Expertise in advanced (probabilistic and statistical) modelling techniques
• Experiences in processing and analyzing complex datasets
• Experiences in scientific computing
Research team: ESSEC CREAR (Center of Research in Econo-finance and Actuarial science on Risk)
Supervisors: The postdoctoral fellow will be co-supervised by Prof. Marie KRATZ (applied probability) and Prof. Juhyun PARK (statistics; ENSIIE & Laboratory of Mathematics and Modeling of Evry – LaMME; email@example.com) and be part of an international and multi-disciplinary team of the ARLES project, having the opportunity to interact and collaborate with other international researchers.
It has long been recognized that the demographics of modern societies are undergoing a fundamental change, with people living longer lives. This has immediate implications for economy and labour force dynamics, as well as the social welfare system. Increasing efforts are being made to improve our understanding of this new phenomenon. As the population, by definition, is a mixture of very heterogeneous entities, it is crucial to characterise the varying experiences of aging in order to understand the needs of individuals and to quantify the impacts of any future policy changes.
Well-designed longitudinal surveys on a national level offer meaningful resources for studying the population trend of the aging process. Longitudinal data analysis is a fundamental tool to understand changes over time, especially, in the context of studying the aging process. The difficulty with working with survey response data is that the aging process is not something that can be measured directly, and we need a careful consideration for modelling and analysis.
Although there are several relevant measurements available related to the aging phenomenon (for instance epigenetic clocks defining the notion of ‘biological age’, or frailty indices), it is difficult or impossible to define what is meant by healthy aging or frailty in general. Aging is a complex process that affects not only the physical and mental but also the emotional well-being of individuals, and these aspects are closely linked. Working at individual level has been made possible thanks to relevant databases available to researches and high dimensional statistical analysis. To deepen our understanding of the factors constituting aging, we require more advanced statistical methodology tofor account for the co-variation and inter-relationships among these factors, of every type (medical, socio-economic, …).
In addition, most studies have focused on the mean process of a single population. Given the nature of the progress each society has made, it is likely that a similar change could occur in different groups of populations in a delayed or transformed time scale. We are interested in capturing such variations of the aging process with the aim of identifying a commonality among those changes.
This proposal is part of a larger international project, named ARLES - Aging Risks and their Long-term impact on the Economy and Society, which aims at developing statistical and probabilistic approaches to understand the relation between health (in broad sense, including socio-economic environment) and aging, looking for indicators to quantify the state of health of aged individuals and relate it to their longevity.
Practical information and how to apply:
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