Job for Researchers overview

Description

Original title: Ingénieur.e d’études en analyse des systèmes alimentaires globaux et leurs impacts

The CNRS (French National Centre for Scientific Research) is recruiting an Ingénieur.e d’études in the analysis of global food systems and their impacts (H/F) for the Laboratoire de géologie de l’École Normale Supérieure in Paris (5th arrondissement). The position is a full-time fixed-term engineering contract (IT, CDD) of 12 months, with a planned start date of 1 September 2026.

About the role

This position is funded by the ERC Starting Grant FLORA – Sustainable and healthy food solutions: system dynamics and trade-offs, led by Carole Dalin at the Department of Geosciences of the École normale supérieure – PSL. The project aims to identify the transformations of food systems needed to reconcile human health with environmental sustainability. The recruited engineer will contribute to the development of prospective scenarios assessing the conditions under which global food systems can evolve within planetary boundaries while ensuring food security, and will take part in the project’s modelling framework and in quantitative analyses of the interactions between agricultural production, food consumption, environment and health.

Responsibilities

  • Develop and analyse transformation scenarios for global food systems.
  • Contribute to the development and use of modelling and quantitative analysis tools, and document code and results on a platform such as GitHub, available to and enriched by all project members.
  • Collect, harmonise and analyse international databases on food systems, agriculture and the environment.
  • Perform statistical analyses and produce visualisations of results.
  • Produce and submit a peer-reviewed scientific publication based on the work carried out within the project.
  • Participate in the drafting of scientific publications and research reports with the FLORA team and other collaborators.
  • Present results at scientific meetings, seminars and conferences.
  • Take part in the scientific life of the FLORA project and collaborate with team members and project partners.

Requirements

Education and experience

Master 2 degree in environmental sciences, geography, agronomy, environmental economics, data science or a related discipline. A prior experience of 1 to 4 years in a relevant field is desired.

Technical skills

  • Quantitative data analysis.
  • Scientific programming in R and/or Python.
  • Mastery of statistical methods.
  • Experience in processing environmental or agricultural data is an advantage.
  • Experience in modelling complex systems or in scenario analysis would be a plus.

Personal qualities

  • Scientific rigour.
  • Autonomy.
  • Team spirit.
  • Analytical and synthesis skills.

Language

Excellent written English and a very good oral command of English.

Working conditions

The recruited person will join an international, interdisciplinary team working at the interface of modelling, data analysis and scenario assessment at the global scale. The work is mainly computer-based and involves handling complex, large datasets. Occasional travel in France and abroad for meetings or conferences is expected.

What we offer

  • Gross monthly remuneration between €2,572 and €3,817.
  • 44 days of annual leave and RTT per year.
  • Teleworking practice and teleworking allowance.
  • Transport costs covered at 75%, plus a sustainable mobility package of up to €300.

Additional information

  • Contract: 12-month fixed-term contract (CDD), full time.
  • Location: 75231 Paris 05, France.
  • Start date: 1 September 2026.
  • Application deadline: Friday 7 August 2026, 23:59.
  • Sector: life, earth and environmental sciences.
  • Reference: UMR8538-CARDAL-004.
  • This offer is open to holders of a title recognising the status of disabled worker.

How to apply

Applications must be submitted before the deadline of Friday 7 August 2026, 23:59.

Original vacancy

Fields of study

Data ScienceEnvironmental SciencesAgricultural SciencesFood SciencesScientific Computing