PhD Position F/M Data assimilation of satellite data in oceanic models, learning of oceanic dynamics

TN France; Rennes; Hybride; EUR 40 000 - 60 000; Plein temps

Résumé du poste

An innovative research group is seeking a motivated PhD candidate to advance the field of ocean dynamics through numerical simulations and machine learning. This exciting position involves developing stochastic models and collaborating with experts in the field to enhance our understanding of ocean behaviors. With a focus on integrating satellite data and high-resolution simulations, you will play a crucial role in shaping future oceanographic research. The role offers flexibility in working hours and the option for teleworking, making it an ideal opportunity for those looking to make a significant impact in environmental science.

Prestations

Partial reimbursement of public transport costs

Option for teleworking (up to 90 days per year)

Flexible hours

Partial insurance cost coverage

Qualifications

• Strong background in applied mathematics, fluid mechanics, or geophysical dynamics.
• Proficiency in programming languages: Fortran, C/C++, Python, and Pytorch.

Responsabilités

• Collaborate with the Odyssey group on stochastic modeling and machine learning.
• Explore data-driven dynamics and hierarchical data assimilation strategies.

Connaissances

Applied Mathematics

Fluid Mechanics

Geophysical Dynamics

Fortran

C/C++

Python

Pytorch

Formation

PhD in Applied Mathematics or related field

Description du poste

Job Description:

The Odyssey team is offering a PhD position focused on numerical ocean dynamics simulation, machine learning, and data assimilation.

Odyssey (for Ocean DYnamicS obSErvation analYsis) is a recently established team involving researchers from Inria (Rennes, France), Ifremer (Brest), and IMT Atlantique (Brest).

Inria is a leading research institute in Computer Sciences in France. Odyssey is affiliated with the mathematics research institute of Rennes University (IRMAR).

The team specializes in mathematical (stochastic) and numerical modeling of ocean flows, observational and physical oceanography, data assimilation, and machine learning.

Their goal is to improve understanding, reconstruction, and forecasting of ocean dynamics, bridging model-driven and observation-driven paradigms to develop new representations of coupled ocean-atmosphere dynamics.

Accurate climatic predictions require plausible forecasts of the ocean state. High-resolution ocean simulations are ideal but currently infeasible due to computational costs, so large-scale representations are used instead.

To address this, the team develops flow models that incorporate noise to account for uncertainties, based on a rigorous theoretical framework called "modelling under location uncertainty," which decomposes flow into resolved and random components, leading to stochastic geophysical flow models.

Models range from multi-layer quasi-geostrophic to primitive equations, with ongoing development of ensemble data assimilation and coupled models.

This PhD position will explore data-driven dynamics from high-resolution data and hierarchical data assimilation strategies to couple stochastic ocean models with satellite data like SWOT.

The candidate will collaborate with the Odyssey group in Rennes and Brest, supervised by Etienne Mémin and co-supervised by Bertrand Chapron and Ronan Fablet, focusing on stochastic modeling, satellite observations, and machine learning for ocean dynamics.

The role involves working within a small group dedicated to ensemble forecasting, learning, and data assimilation, with collaborations across related research groups and projects.

Applicants should have a strong background in applied mathematics, fluid mechanics, or geophysical dynamics, and proficiency in Fortran, C/C++, Python, and Pytorch.

Advantages include:

• Partial reimbursement of public transport costs
• Option for teleworking (up to 90 days per year) and flexible hours
• Partial insurance cost coverage

Salary: €2100/month for the first two years, increasing to €2200/month in the third year.