AI Scientist – Domain Expert, Crashworthiness

This is a fully remote position, open to applicants in France.

📋 Description

• Define, create, and continuously enhance simulation datasets for crashworthiness foundational models.

• Design and execute high-fidelity simulation campaigns utilizing structural mechanics solvers.

• Establish variation spaces that encompass geometry, mesh resolution, material behavior, boundary conditions, loading, contact, joints, failure modes, and engineering KPIs.

• Construct or oversee automated pipelines for simulation setup, execution, post-processing, dataset creation, and model assessment.

• Collaborate with research teams to train and evaluate AI models using simulation data.

• Identify failure modes resulting from data deficiencies, inadequate coverage, numerical artifacts, or model constraints.

• Assess model outputs against industrial engineering requirements, including accuracy, KPIs, deformation modes, load paths, energy absorption, stress/strain fields, failure indicators, uncertainty, and out-of-domain behavior.

• Partner with industrial clients to comprehend workflows and priorities, define use cases and success criteria, and integrate feedback into model development and validation.

⛳️ Requirements

• Extensive expertise in crashworthiness, solid mechanics, and structural mechanics.

• Master’s degree or equivalent technical knowledge in mechanical engineering, aerospace engineering, civil/structural engineering, computational mechanics, applied physics, or a related discipline.

• A minimum of 4 years of relevant industrial experience, or a PhD with an additional year of experience.

• Practical experience with explicit dynamics for crash or impact simulation.

• Proficiency in nonlinear FEM, contact, plasticity, structural dynamics, buckling, material modeling, fracture/damage, fatigue, crashworthiness, or durability.

• Experience in simulation validation, correlation, model quality, numerical sensitivity, and defining engineering KPIs.

• Strong skills in Python development.

• Familiarity with software engineering practices including Git, automated testing, code reviews, and documentation standards.

• Hands-on experience in Linux and HPC environments.

• Experience with submitting and monitoring batch jobs, selecting computational resources, and troubleshooting simulation workflows.

• Capability to execute simulation campaigns across a computing cluster.

• Ability to transform vaguely defined industrial problems into well-scoped datasets, experiments, metrics, and execution strategies.

• Effective communication with both technical experts and non-specialist stakeholders.

🏝️ Benefits

• Healthcare coverage.

• Parental leave.

• Retirement plans.

• Relocation support.

• Wellness programs.

• Meal allowances.

• Transportation allowances.

• Additional location-specific perks.