Quantitative knowledge synthesis for the analysis of climate risks related to agriculture

Article published on January 28 2020 , Updated on January 28 2020
  • Type d'offre et durée du contrat
    Offres d’emploi

    Candidates should send to cland@lsce.ipsl.fr before January 31, 2020 :

    • A detailed CV
    • A list of publications
    • A letter explaining the fit to the profile with a draft of the research project (3 pages max)

    Applicants who will have been selected will be notified by February 10, 2020 and will be invited to an interview at University of Paris-Saclay in the second half of February 2020 (it is foreseen a presentation of 20 minutes with 40 min of questions).

    The result of the interview will be communicated by March 6, 2020. The position is expected to start two to three months later.

  • Rémunération
    The scientist will be recruited on permanent contracts by the University of Paris-Saclay. Salary according to CV.
  • Localisation
    The successful candidate will be attached to the INRA-AgroParisTech ECOSYS UMR (currently in Grignon, will move to the campus of Paris-Saclay in 2021).

Description du poste

The University of Paris Saclay and the CLAND Convergence Institute open a permanent position for a young experienced engineer / researcher to contribute to research projects focused on the impacts of climate change on agriculture and the contribution of agricultural activities to greenhouse gas emissions and carbon storage.
 

Missions

The successful candidate will carry out quantitative analysis of experimental or simulation datasets to estimate variables of significant scientific and/or societal value (e. g. effect of a temperature increase on biomass production, estimation of the effectiveness of methods for offsetting greenhouse gas emissions), or to make predictions useful for decision-making (e.

g. inventories of N2O or methane emissions, prediction of agricultural yields as a function of climate variables). The results of these quantitative analyses can be used in scientific articles, international expert reports, decision support tools and policy briefs useful for public decision-making.

A rigorous synthesis of the available data, however, poses different methodological and practical problems. The successful candidate will mobilize advanced methods of quantitative knowledge synthesis, including meta-modelling, machine learning and meta-analysis, to understand and quantify the impact of climate change on agriculture (on crop yields, quality and cropping areas) and greenhouse gas (N2O, methane, CO2) balances in agro-ecosystems. He/she will use these methods to develop international expertise in knowledge synthesis on climate risks.

This position aims not only to make a significant contribution to academic research in this field but also to generate products of collective scientific interest, in particular: publicly accessible databases via data papers, data challenges organized to develop predictive algorithms on strategic subjects, simple mathematical models developed by machine learning that can be easily reused, international data science trainings and workshops for climate risk analysis. It is also intended to provide methodological support to doctoral and post-doctoral students involved in the CLAND Convergence Institute, which the recruited scientist will help to supervise. The successful candidate will collaborate with colleagues specialized in applied mathematics, econometrics, crop and greenhouse gas emission modelling, climate science.

Requirements

  • A doctoral degree and several years of postdoctoral experience.
  • Several publications in international peer-reviewed journals on the subject of the position.
  • Strong experience in the use of statistical models, machine learning methods and/or meta- analysis to analyze complex databases.
  • An excellent knowledge of one or more programming language for data analysis (R, Python).
  • A strong interest in environmental and agricultural issues on a large scale (continental and global).
  • A network of international collaborators on the subject of the position.
  • A capacity to supervise technical staff, students and doctoral fellows.

 

  • An ability to set up research projects and work as a team, and within a research network such as the CLAND Convergence Institute.

Modalités pour postuler

Candidates should send to cland@lsce.ipsl.fr before January 31, 2020 :

  • A detailed CV
  • A list of publications
  • A letter explaining the fit to the profile with a draft of the research project (3 pages max)

Applicants who will have been selected will be notified by February 10, 2020 and will be invited to an interview at University of Paris-Saclay in the second half of February 2020 (it is foreseen a presentation of 20 minutes with 40 min of questions).

The result of the interview will be communicated by March 6, 2020. The position is expected to start two to three months later.