AI Scientist - Physics Models

Mistral; Linz; Vor Ort; EUR 90.000 - 120.000; Vollzeit

Benefits dieser Stelle

Healthcare coverage

Relocation support

Meal and transportation allowances

Zusammenfassung

Mistral is seeking AI Scientists to push the frontier of AI-accelerated simulation, researching and training foundational physics models that can be fine-tuned for downstream applications. You will curate high-fidelity simulation data, design novel architectures, and rigorously evaluate them against engineering validation standards.

You’ll work across the full research stack, ensuring models are general enough to serve as backbone for multiple downstream products, with a focus on uncertainty

Qualifikationen

• PhD or Master’s in CS/AI or engineering science.
• Strong ML expertise with model architectures, training dynamics, and evaluation.
• Experience developing ML methods for simulation or surrogate modelling.
• Proficient Python coding; comfortable in Linux/HPC environments.
• Fluent English with excellent communication skills.
• Self-directed and collaborative.

Aufgaben

• Research and train novel foundation models for physics simulation, pushing past today’s state of the art in accuracy, generalization, and scale.
• Design and run large-scale simulation campaigns using domain-specific solvers to build high-fidelity datasets.
• Investigate architectures and training strategies that enable a single foundation model to transfer across diverse engineering tasks.
• Rigorously evaluate model coverage, accuracy, and robustness against validation standards.
• Stay on top of the latest developments and contribute to Mistral’s standing at the frontier of AI-for-engineering research.

Kenntnisse

Machine learning

Python

Surrogate modelling

Engineering physics

Communication

Self-directed

Ausbildung

PhD in CS/AI or Engineering Science

Master’s in CS/AI or Engineering Science

Tools

OpenFOAM

LS-DYNA

Abaqus

COMSOL

NekRS

Jobbeschreibung

About Mistral

Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems—across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector—co-creating customized AI systems that they can run on their terms.

We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.

The Role

Mistral is looking for AI Scientists with deep expertise in engineering sciences and machine learning to push the frontier of AI-accelerated simulation. Within AI4Engineering Science, you will research and train foundational physics models which are substantially more capable than what exists today and can be fine-tuned for downstream applications by both customers and internal teams.

You will work across the full research stack: curating high-fidelity simulation datasets, designing and training novel model architectures, and rigorously evaluating them against real engineering validation standards.

Working closely with the broader research organization, you’ll ensure the foundation models you build are general enough to become the backbone of many downstream products, not just a single point solution.

This role builds on a strong, world-class foundation, and the goal is to take it further. You’ll work one vertical at a time toward foundation models that genuinely transfer and fine-tune across engineering tasks, with high-quality simulation data pipelines, physics-based evaluation, and uncertainty / out-of-distribution estimation as first‑class concerns. There’s no inherited playbook for most of what’s left to do: you’ll help define the architectures, training strategies, and validation standards the team builds on, not just extend an existing one.

What You Will Do

• Research and train novel foundation models for physics simulation, pushing past today’s state of the art in accuracy, generalization, and scale

• Design and run large-scale simulation campaigns using domain‑specific solvers to build the high‑fidelity datasets foundational physics models need

• Investigate architectures and training strategies (e.g. multi‑fidelity training, pretraining objectives, scaling behavior) that let a single foundation model transfer and fine‑tune well across diverse engineering tasks

• Rigorously evaluate model coverage, accuracy, and robustness against industry validation standards, and diagnose failure modes arising from data gaps or architecture limitations

• Stay on top of the latest developments in the scientific community and contribute to Mistral’s standing at the frontier of AI‑for‑engineering research

What We’re Looking For

• PhD or Master’s in CS/AI or an engineering science: Mechanical Engineering, Electrical Engineering, Computational Fluid Dynamics, Structural Mechanics, EDA, Semiconductor Engineering, or a related field

• Strong, hands‑on machine learning expertise with a deep understanding of model architectures, training dynamics, and evaluation methodology is core to this role

• You have developed ML methods for simulation or surrogate modelling

• You write clean, readable Python code and are comfortable in Linux/HPC environments

• Fluent English with excellent communication skills, able to explain technical simulation and ML concepts to both engineering and non‑technical audiences

• 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 industrial or academic experience with simulation solvers (e.g. OpenFOAM, LS‑DYNA, ANSYS, COMSOL, Abaqus, Fluent, STAR‑CCM+, PowerFlow, NekRS, Tau/CODA, JAX‑Fluids, or equivalent; Cadence/Synopsys/Siemens EDA or equivalent)

• 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 (AIAA, ASME, JFM, NeurIPS, ICLR, etc.)

What We Offer

We offer a comprehensive benefits package designed to support your well‑being, growth, and work‑life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location‑specific perks.

For the most up‑to‑date details on benefits available in your location, please refer to our Benefits page.

Privacy Policy

Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy.