Location: Laboratoire d'Océanographie Physique et Spatiale (LOPS), IUEM, Université de Bretagne Occidentale, Plouzané, France
Duration: 2 years
Start date: Flexible, before the end of 2026.
Eligibility condition: Applicants must have spent at least 18 months outside of France between May 1, 2022, and the start of the project.
The deep ocean remains one of the least explored regions on Earth, yet deep-sea currents—especially near the seafloor—play a crucial role in regulating global climate, transporting sediments, and sustaining benthic ecosystems. Despite advances in satellite observations of the ocean surface, our understanding of these currents is limited by sparse in-situ measurements and the coarse resolution of most ocean models.
This postdoctoral project aims to advance knowledge of the structure and variability of deep ocean currents and to develop machine learning tools to reconstruct and predict them, including extreme events such as benthic storms. The research will combine in-situ observations from a mooring database, high-resolution numerical simulations, and surface-observable data. It will focus on characterizing the statistical properties of deep currents, identifying their main drivers, evaluating how well different classes of models represent these processes, and ultimately developing predictive models based on surface measurements and bathymetry.
The postdoctoral researcher will work with high-resolution simulations (GIGATL1, LLC4320), global reanalyses (SODA, GLORYS12, ECCO), observational datasets, and state-of-the-art machine learning techniques to create an emulator capable of reconstructing both instantaneous currents and their statistical features. This approach will provide new insights into deep-sea current dynamics and generate practical tools for oceanographic, ecological, and sediment transport studies.
Applicants should submit:
Deadline: Applications will be reviewed until the position is filled.