Applied Scientist / Domain Expert, AI4Engineering - EMEA

What you will do

• Design and run large-scale simulation campaigns using domain-specific solvers (e.g. OpenFOAM, ANSYS, COMSOL, Abaqus)
• Run training of AI models on physics data, with rigorous evaluation of coverage, accuracy, and quality against industry validation standards
• Build tools and frameworks for automated dataset creation, simulation pipeline management, and model evaluation
• Collaborate closely with the science/research team on training runs and diagnose failure modes arising from data gaps or architecture limitations
• Manage research projects and client communications with engineering teams

About you

• Fluent English with excellent communication skills - able to explain technical simulation concepts to both engineering and non-technical audiences
• Have a PhD in physics or engineering and 5 years+ of industry experience in a relevant domain. You work in a key engineering industry: Automotive, Aerospace or Semiconductors and have an interest in machine learning.
• Self-directed - you don't need detailed roadmaps to make progress
• Low-ego, collaborative, and eager to learn at the intersection of simulation and ML
• Demonstrated success through industrial projects, academic work, or personal projects

It would be great if you

• Have a deep passion for machine learning
• Have industrial or academic experience with simulation solvers (e.g. OpenFOAM, ANSYS, COMSOL, Abaqus, or equivalent)
• Have applied ML methods to simulation or surrogate modelling
• Have experience automating large-scale simulation campaigns on HPC clusters
• Have contributed to a large open-source or industry codebase
• Have publications in engineering or ML venues (NeurIPS, ICLR, etc.)
• Love improving existing code by fixing typing issues, adding tests and improving CI pipelines