Applied Scientist / Domain Expert, AI4Engineering - EMEA

• 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

• 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

Nice to have

• 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