Simulation Engineer - Thermal Process

As a Senior Simulation Engineer (Delivery), you are a problem solver and a builder, who is passionate about creating practical solutions that enable customers to make better engineering decisions. You are someone who can grasp and apply advanced engineering concepts across multiple industries, and you excel at working directly with customers (often directly on-site) to build CAE models that are integrated into AI-tools that are both useful and used.

You bring deep expertise in metallurgical, chemical, heat transfer, and multiphase modelling, with a solid ability to apply fundamental knowledge to real-world phenomena across a wide range of engineering applications. Highly proficient in at least one of Abaqus, ANSYS Mechanical/Fluent, and adept at automating these tools to create scalable optimisation workflows that drive impactful results. Experience in parametric CAD modelling (NX, FreeCAD or CATIA) and coding in Python/Java, (or the ability to quickly learn programming languages).

With industrial / line-side / manufacturing process experience in a commercial, non-research environment, you're ready to hit the ground running. You're confident setting up simulations independently, interpreting complex results with depth, and making informed decisions based on solid engineering judgement.

In this role, you'll work alongside our Data Scientists, Machine Learning Engineers, and (with support) our customers to help define and solve engineering challenges.

• Deep proficiency in thermal and heat-transfer simulation across platforms (Abaqus, ANSYS Mechanical/Fluent, COMSOL, or equivalent), including conduction, convection, radiation, and transient heat-transfer modelling with temperature-dependent material properties
• Deep proficiency in coupling thermal, chemical, fluid, diffusion, and electrostatic phenomena
• Strong grasp of numerical methods and solver fundamentals — discretisation schemes, convergence behaviour, stability, mesh sensitivity, and the judgement to diagnose non-physical results rather than accept solver output at face value
• Instrumentation design and real-world data collection — instrumenting physical processes (sensors, test rigs, in-situ measurement) to generate validation data for processes that have no existing simulation capability
• Hands-on, real-world experience on the shop floor with manufacturing plants, industrial engineering processes, and/or repair operations — not simply desk-based familiarity
• Awareness of qualified-process and regulatory constraints — understanding that model outputs must respect qualified parameter windows, and distinguishing optimisation within a qualified window from changes that trigger requalification
• Customer-facing delivery — partnering with client process owners to scope and address complex repair challenges; communicating results clearly and balancing accuracy with efficiency under commercial deadlines