PhD in Stochastic Ocean Modelling & Inverse Problems

1000scholars; Rennes; On-site; EUR 23,000 - 28,000; Full time

Job summary

Inria Rennes, within the Odyssey team, invites applications for a PhD thesis on modelling under location uncertainty in geophysical fluid dynamics. The work combines stochastic modelling, inverse problems, and numerical simulation of deep convection in ocean models using CROCO.

Collaboration with multiple teams will enrich the research environment. The candidate will develop theory, implement algorithms (adjoint and ensemble methods), and assess covariance estimation against reference

Qualifications

• Background in applied mathematics, fluid mechanics, or oceanography.
• Strong interest in numerical simulation.
• Basic programming skills in Python or Julia and Fortran or C++ would be an advantage.

Responsibilities

• The candidate will work with stochastic models for deep convection.
• Implement reference simulations using the CROCO model.
• Formulate inverse problems to determine covariances of stochastic noise.
• Explore adjoint and ensemble methods for parameter estimation.
• Assess scalability on high-dimensional ocean models.

Skills

Applied mathematics

Fluid mechanics

Oceanography

Numerical simulation

Python

Julia

Fortran

C++

Tools

Python

Julia

Fortran

C++

Job description

Inria Rennes, within the Odyssey team, invites applications for a PhD thesis on modelling under location uncertainty in geophysical fluid dynamics. The work combines stochastic modelling, inverse problems, and numerical simulation of deep convection in ocean models using CROCO.

Collaboration with multiple teams will enrich the research environment. The candidate will develop theory, implement algorithms (adjoint and ensemble methods), and assess covariance estimation against reference