This position is part of Williams Grand Prix Technologies, a Williams Group company.

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.