Marie Skłodowska-Curie Actions

Université Claude Bernard Lyon 1- Hosting offer for an MSCA-IF post-doc candidate in Mathematical Statistics and Machine Learning

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    23/07/2019 15:30 - Europe/Athens
    H2020 / Marie Skłodowska-Curie Actions
    France, Villeurbanne
    Université Claude Bernard Lyon 1
    Actuarial Science and Finance Institute
    Laboratory of Actuarial Science and Finance

The Laboratoire de Sciences Actuarielle et Financière (LSAF) is a leading actuarial research lab in Europe and undertakes inter-disciplinary research on risks in insurance and finance. The research topics of the laboratory are always evolving to include new risks (human longevity improvements, natural hazards...), recent accounting standards (IFRS), new prudential regulation systems (Basel 4, Solvency 2) as well as new risk management practices (Enterprise Risk Management) or new business models with Big Data and Analytics in insurance. Current team research projects concern in particular the impact of modeling and data analytics on the management of insurance and financial firms, environmental risks, longevity risk management and public health, long term investments and ESG, as well as behaviours and risks.

Strongly associated to ISFA graduate school of actuarial studies, LSAF gathers 30 permanent researchers, 4 post-docs and 18 PhD students. LSAF is part of University Claude Bernard Lyon 1 (UCBL), a multidisciplinary university in the primary fields of science and health. With over 2630 professors and assistant professors and 39,000 students, leading to more than 4500 internationally published articles and 40 patents per year. The University is involved in more than 80 European Union projects.

The LSAF offers to host a MSCA Individual Fellowship candidate ("Experienced Researcher" according to the Marie Sklodowska Curie categories, typically a post-doc), submitting an application to the next MSCA-IF call for proposals (deadline september 2019), interested to work on the following research topic:

Extremal Quantile Regression Tree and Forests

Quantile regression forests were introduced as a machine learning tool in Meinshausen (2006) and have since proven to be very powerful for quantile high-dimensional regression. At the same time, extremal quantile regression were also introduced by Chernozhukov (2005) to provide a theory of quantile regression in the tails. Such regressions are however only suited for moderate sized covariates. Although random forest-based post-processing techniques in compliance with Extreme Value Theory have been proposed to improve prediction behind the largest values of a sample, no theoretical result has been provided to assess the validity of the approach. The main objective of this project is to study from a theoretical point of view whether regression trees and forest can also be used to infer extremal quantiles in the presence of high dimensional covariates.

Chernozhukov, V. (2005). Extremal quantile regression. Annals of Statistics. 33 (2), 806–839.

Meinshausen, N. (2006). Quantile Regression Forests. Journal of Machine Learning Research 7 (2006) 983–9.

We are looking for a candidate with a strong background in mathematical statistics or in Machine Learning. Her/his PhD defense must take place before Sept. 10th, 2019. The fellowship could last for 12 to 36 months, depending on the type of Individual Fellowship.


The successful Marie-Curie Post-doctoral fellow will be supervised by Christian ROBERT at LSAF, UCBL and will also work with Johan SEGERS at UCLouvain.

Christian ROBERT is professor at ISFA, UCBL. His research interests include extreme value theory and statistics, actuarial sciences, and data analytics. https://isfa.univ-lyon1.fr/recherche/membres-du-laboratoire/christian-ro...

Johan SEGERS is professor at the Institut de statistique, biostatistique et sciences actuarielles of the Université catholique de Louvain. His research interests include applied probability, extreme value theory, dependence modelling via copulas. https://perso.uclouvain.be/johan.segers/.

Application process to LSAF:

Interested candidates are invited to contact us exclusively by email at postdoc-1914@isfa.fr

Make sure that you include the reference "Post-doc 1914" in the title of your email. Please attach a CV, a motivation letter, your MSc marks, as well as a 1-page research proposal.

NB: Candidates will receive the support of the LSAF supervisors, as well as a professional grant application company, to prepare and submit their application with the LSAF as a host laboratory, to the next MSCA-IF call for proposals.






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