OFFER DEADLINE10/08/2019 16:30 - Europe/Athens
EU RESEARCH FRAMEWORK PROGRAMMEH2020 / Marie Skłodowska-Curie Actions
ORGANISATION/COMPANYUniversité Claude Bernard Lyon 1
DEPARTMENTActuarial Science and Finance Institute
LABORATORYLaboratory 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:
Ensemble methods such as Random forest were initially designed to take into account the impact of fixed covariates on one given observed response. However, there are numbers of applications where one needs to consider not only the observed value of explanatory variables at some point, but also its evolution. Some simple practical solutions do exist, but there still lacks developments on how to integrate such risk factors in the modelling process, as well as how to measure the impact of the latter choice in terms of prediction accuracy. The present project thus consists in investigating how to appropriately consider time-dependent explanatory variables in statistical learning algorithms, with applications to finance and insurance.
Short bibliography :
Möller, A., Tutz, G. and Gertheiss, J. (2016): Random Forests for functional Covariates. Journal of Chemometrics 30 (12), 715-725.
We are looking for a candidate with a strong background in data science and/or statistics. 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 Xavier Milhaud.
Xavier Milhaud is associate professor at ISFA, UCBL. His main research interests include finite mixture models, regression models, and Machine Learning algorithms applied to insurance risks. The typical applications of his works concern customer behaviour in insurance, as well as pricing and reserving models in actuarial sciences.
See more at http://xaviermilhaud.fr/en/index-en.html
Application process to LSAF:
Interested candidates are invited to contact us exclusively by email at firstname.lastname@example.org
Make sure that you include the reference "Post-doc 1911" 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.
The responsibility for the hosting offers published on this website, including the hosting description, lies entirely with the publishing institutions. The application is handled uniquely by the employer, who is also fully responsible for the recruitment and selection processes.