29/03/2019
Marie Skłodowska-Curie Actions

Université Claude Bernard Lyon 1- Hosting offer for an MSCA-IF post-doc candidate in Actuarial and Data Science


  • OFFER DEADLINE
    27/07/2019 12:30 - Europe/Athens
  • EU RESEARCH FRAMEWORK PROGRAMME
    H2020 / Marie Skłodowska-Curie Actions
  • LOCATION
    France, Villeurbanne
  • ORGANISATION/COMPANY
    Université Claude Bernard Lyon 1
  • DEPARTMENT
    Actuarial Science and Finance Institute
  • LABORATORY
    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:

Targeted learning is a novel approach in data science, see Van Der Lann and Rose (2018). It has been applied successfully to the study of longitudinal data and repeated measurements in biostatistics. This project aims at looking into the application of this methodology to actuarial science problem such as risk capital allocation and insurance policies ratemaking. We are looking for a candidate with a strong background in actuarial science and statistics. The applicant should have demonstrated the ability to publish his/her work in peer reviewed journals and have strong coding skill R. Her/his PhD defense must take place before Sept. 10th, 2019.

Van der Laan, M. J., & Rose, S. (2018). Targeted learning in data science: causal inference for complex longitudinal studies. Springer.

The fellowship could last for 12 to 36 months, depending on the type of Individual Fellowship.

Supervision:

The successful Marie-Curie Post-doctoral fellow will be supervised by Pierre-Olivier Goffard.

Pierre-Olivier Goffard is associate professor at ISFA, UCBL. His research interests include data science, risk theory and actuarial science. http://pierre-olivier.goffard.me/

Application process to LSAF:

Interested candidates are invited to contact us exclusively by email at postdoc-1922@isfa.fr

Make sure that you include the reference "Post-doc 1922" 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.

Disclaimer:

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.