Senior Modelling and Simulation Engineer presso Williams Racing

Established in 2024 and based alongside Atlassian Williams Racing in Grove, UK, Williams Grand Prix Technologies is driving innovation with pedigree. We offer world-leading capabilities in platform dynamics, advanced materials, simulation intelligence, prototyping, and testing. Drawing on nearly five decades of unrivalled engineering prowess earned at the forefront of motorsport and advanced engineering, we solve complex challenges across aerospace, premium automotive, defence, sport, and lifestyle sectors. Powered by a motorsport heritage demanding precision and speed, we deliver tailored, high-performance solutions that push boundaries and accelerate progress. 

We are seeking a Senior Modelling and Simulation Engineer with a specialisation in multi-physics systems engineering. This role involves leading the development of advanced system models that span mechanical, electrical, thermal, and fluid dynamics domains. You will leverage cutting-edge simulation tools such as MATLAB, Simulink, Simscape, and JuliaHub to create high-fidelity models and run simulations to solve complex engineering challenges across a range of industries.

This position requires expertise in co-simulation techniques, where multiple physical domains are integrated to achieve system-level optimisation. As a senior engineer, you will guide technical projects from inception to completion, mentor junior engineers, and collaborate with cross-functional teams to drive innovation and streamline workflows. 

Key Responsibilities 

• Develop, refine, and validate multi-physics models to accurately represent complex systems, encompassing domains such as mechanical, electrical, thermal, and fluid dynamics. 

• Utilise advanced modelling tools such as MATLAB, Simulink, and Simscape, (or equivalent i.e. Dymola, Modelica) and JuliaHub to create, simulate, and optimise high-fidelity physical models. 

• Integration of physical and machine learning models to deliver high-accuracy estimation and insights.

• Maturation of simulation toolchain and co-simulation framework to conduct holistic system-level analyses.

• Automate and optimise simulation workflows to accelerate model development and integration with parametric CAD models and streamline the design process.

• Leverage both on-premise high-performance computing (HPC) and cloud computing resources to enhance simulation efficiency, ensuring accurate results within reduced timeframes.

• Responsible for leading technical work packages, collaborating with interdisciplinary teams, ensuring timely delivery and high-quality outcomes, while also mentoring and guiding junior engineers in the team.

• Maintain a high standard of engineering best practices, continuously seeking improvements and fostering their adoption within the team.

About You:

• Bachelor's or Master's degree in Mechanical Engineering, Electrical Engineering, or a related field with an emphasis on multi-physics simulation and systems engineering; PhD preferred. 

• Extensive experience in multi-physics systems engineering, including hands-on expertise in: 

  • Advanced tools such as MATLAB, Simscape, JuliaHub, and equivalents (e.g., Dymola, Modelica). 

  • Co-simulation frameworks for integrating multiple domains. 

  • Building models from scratch, including geometry preparation, parameterisation, and post-processing. 

  • Applying systems engineering principles across mechanical, thermal, electrical, and fluid domains. 

  • Automating simulation workflows, including CAD integration for optimisation. 

• Practical experience with Scientific Machine Learning (SciML) using MATLAB, JuliaHub, and equivalents, embedding ML into physics-based models.

• Strong background in data science and machine learning, with proven ability to integrate data-driven and physics-based approaches for improved prediction accuracy.

• Expertise in model validation and correlation with experimental or real-world data.

• Strong analytical and problem-solving skills, with ability to identify root causes and implement effective solutions.

• Excellent communication and collaboration skills, with experience working in cross-functional teams.

• Passion for mentoring and developing junior engineers, fostering a culture of technical excellence

Preferred Skills:

• Proven expertise in high-performance computing (HPC) environments for running large-scale simulations and optimising computational efficiency.
• Proficiency in Python and/or Java, for scripting and workflow automation.
• Hands-on experience in multi-domain optimization techniques, particularly for real-time decision-making in high-performance applications such as motorsports, aerospace, or automotive industries.
• Publications or patents in the fields of multi-physics simulations, scientific computing, or AI-driven engineering solutions.

Why join us? 

Williams Grand Prix Technologies is based at the Williams Racing Campus in Grove, Oxfordshire, a cutting-edge, expansive facility just 30 minutes from Oxford city centre by bus. 

We fuel our team with a competitive benefits package, including generous holidays, vibrant staff events, a subsidised onsite restaurant, and a range of car schemes. Stay energised with 24/7 access to our gym and free fitness classes like outdoor boot camps, Pilates, and yoga. With free parking and sprawling green spaces, you’ve got the perfect space to recharge and refocus. 

Join a fast-paced, future-thinking team that’s driving innovation and pushing past engineering boundaries. Here, your skills and ideas don’t just contribute, they will power projects across diverse industries, making a real global impact.

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Atlassian Williams Racing is an equal opportunity employer that values diversity and inclusion. We are happy to discuss reasonable job adjustments.