How we work
Make decisions from results
When several approaches are possible, we compare them through reproducible experiments and against criteria defined in advance.
Make negative results visible
Experiments that fail or produce insufficient results are documented just like positive ones. They help guide subsequent development.
Understand the methods
We try to understand the source of a numerical behavior before changing a method or its parameters.
Ensure reproducibility
Simulation campaigns, experiments, and code are documented so that another member of the team can review, verify, and reproduce them.
The profiles we are looking for
Numerical analysis
Finite elements, iterative methods, preconditioning, model reduction. You know why a solver stalls.
Learning and physics
SciML, constrained learning, transfer across tasks. You are cautious about models whose outputs cannot be verified.
Scientific software engineering
High-performance computing, traceability, reproducibility. You care about being able to reproduce a result exactly.
Interested in talking?
Tell us what you can do and what kind of problem you would like to work on. We do not require you to fit a predefined job description: we read every application and reply.
Stay informed
Our technical updates and publications. No marketing emails.
Inria Saclay
École polytechnique campus
1 rue Honoré d’Estienne d’Orves
91120 Palaiseau, France
