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CNRS

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PhD Position in Data-Driven Reduction of Nonlinear PEM Fuel Cell Models CNRS in France

Degree Level

PhD

Field of study

Mechanical Engineering

Funding

Available

Deadline

Dec 1, 2026

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Country

France

University

CNRS

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Keywords

Mechanical Engineering
Electrical Engineering
Mathematics
Linear Algebra
Dynamic Systems
Nonlinear Systems
Multiphysics Simulation
Fuel Cell
Physics

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About this position

This PhD project is part of H2-TWIN and focuses on building fast, reliable reduced-order models for PEM fuel cell systems from a high-fidelity multiphysics model. The goal is to make these models suitable for real-time simulation, control, monitoring, and system sizing.

The doctoral research is centered on data-driven, non-intrusive model reduction, with the Loewner framework as the main methodological base. A key challenge is to extend this framework to the nonlinear structure of fuel-cell models while preserving the multiphysics couplings and physical interpretability of the original system.

The PhD student will work on identifying the nonlinear terms in the project’s high-fidelity models, developing structure-preserving reduction methods, and applying them to obtain efficient reduced models. These models will be evaluated for accuracy, computational cost, and suitability for real-time simulation, control, diagnosis, and sizing.

The project also includes the development of methods to recalibrate reduced models using experimental measurements, both offline and online, to account for system evolution such as aging or faults. Validation will use data from the Toulouse Hydrogen Platform or open datasets.

The expected outcome is an open-source implementation of new structure-preserving reduction methods for nonlinear multiphysics systems, together with reduced PEM fuel cell benchmarks of varying complexity and related calibration methods. The work is set within an applied, computational research context tied to hydrogen and fuel-cell modeling.

Funding details

Available

What's required

Master’s degree or engineering diploma in applied mathematics, scientific computing, automation, or electrical/energy engineering is required. Strong foundations in numerical linear algebra, dynamical systems (state-space representations, transfer functions, frequency responses), and numerical methods for ODEs and PDEs are required. Good programming skills in Python and/or MATLAB are required. A good level of written and spoken English is required; French is not necessary. Autonomy, rigor, curiosity, and the ability to work in a team are expected.

How to apply

Apply through the official CNRS job portal using the application link provided. Review the full advert and prepare the requested application materials before the deadline. Submit your application online by 2026-12-01.

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