Florian Ricour

Florian Ricour

Data Scientist · Research Engineer · PhD in Oceanography

I build data pipelines, visualizations, and interactive applications for environmental science. With a background in oceanography and experience across research institutions, I help teams turn complex datasets into reliable, usable results.

Belgium

Experience

Freelance — Science Developer

Remote

Jan 2025 – Present
  • Integration of new classes for computing nutrients using Biogeochemical-Argo data in the argopy Python package with IFREMER
  • Development of a Shiny for Python application for Delayed-Mode Quality Control on Biogeochemical-Argo, deployed on remote servers (LOV)

Research Engineer

Royal Belgian Institute of Natural Sciences — Brussels

Jan 2024 – Present
  • Reproducible data pipelines integrating heterogeneous climate datasets (Biogeochemical-Argo, EMODnet, CMEMS, C3S) for biogeochemical model simulations
  • Decision-making web applications for stakeholders — ecosystemic services within ocean wind farms
  • Development of a generic coupler for biogeochemical models and the COHERENS model using FABM
  • Numerical and machine learning models deployed on HPC clusters.

PhD Fellow

F.R.S.-FNRS — Brussels

Oct 2019 – Sep 2023
  • Embedded computer vision algorithm for near real-time zooplankton classification
  • Reassessment of global carbon sequestration — published in Nature Geoscience
  • Study of carbon export using underwater cameras and optical sediment traps onboard Biogeochemical-Argo floats data

Researcher

University of Liège

Oct 2018 – Sep 2019
  • Reassessment of dissolved oxygen content in the world ocean by building a new oxygen climatology from heterogeneous observational datasets

Education

PhD in Oceanography

University of Liège & Sorbonne University

2019 – 2023

Towards a new insight of the carbon transport in the global ocean

MSc in Oceanography — Summa cum laude

University of Liège

2016 – 2018

Albert Distèche award for best master thesis in oceanography

BSc in Applied Science — Cum laude

University of Liège

2013 – 2016

Major in Physics and Electronics

Skills

Programming & Tools

Python R Shiny Quarto Git HPC Linux

Data Science & ML

Machine Learning Deep Learning Statistical Modeling Computer Vision

Selected Publications

Ricour, F., Guidi, L., Gehlen, M., DeVries, T. & Legendre, L. (2023). Century-scale carbon sequestration flux throughout the ocean by the biological pump. Nature Geoscience, 16, 1105–1113.

DOI

Terrats, L., Claustre, H., Briggs, N., Poteau, A., Briat, B., Lacour, L., Ricour, F., Mangin, A. and Neukermans, G. (2023). Biogeochemical-Argo floats reveal stark latitudinal gradient in the Southern Ocean deep carbon flux. Global Biogeochemical Cycles, 37(11).

DOI

Ricour, F., Capet, A., d'Ortenzio, F., Delille, B., & Grégoire, M. (2021). Dynamics of the deep chlorophyll maximum in the Black Sea as depicted by BGC-Argo floats. Biogeosciences, 18(2), 755–774.

DOI

Full list on ORCID

Achievements

Copernicus Hackathon Winner

Detection of acid mine drainage using satellite imagery — Brussels

Copernicus Accelerator

1 year of mentoring: product prototyping, pitching, research-to-business transition

PARSEC — Project EXAMINE

EU-funded software prototype for detecting acid mine drainage using Copernicus data