Simulation Engineer - Electromagnetic Specialist

Shoreditch, London
Simulation Engineering /
Full-time /
Hybrid
PhysicsX is a deep-tech company of scientists and engineers, developing machine learning applications to massively accelerate physics simulations and enable a new frontier of optimisation opportunities in design and engineering.

Born out of numerical physics and proven in Formula One, we help our customers radically improve their concepts and designs, transform their engineering processes and drive operational product performance. We do this in some of the most advanced and important industries of our time – including Space, Aerospace, Medical Devices, Additive Manufacturing, Electric Vehicles, Motorsport, and Renewables. Our work creates positive impact for society, be it by improving the design of artificial hearts, reducing CO2 emissions from aircraft and road vehicles, and increasing the performance of wind turbines.

We are a rapidly growing and profitable company but prefer to fly under the radar to protect our customers’ confidentiality. We are about to take the next leap in building out our technology platform and product offering. In this context, we are looking for a capable and enthusiastic simulation engineer to join our team. If all of this sounds exciting to you, we would love to talk (even if you don't tick all the boxes).

Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.

Position Overview
We are seeking a skilled Electromagnetic Simulation Expert with a strong focus on high-frequency electromagnets applications such as radio antenna design, induction heating processes, wireless charging systems. The ideal candidate will possess a deep understanding of electromagnetics, particularly Maxwell's equations, and the underlying physical mechanisms. Working with us offers a unique opportunity to help shape how AI is transforming the simulation landscape and be at the front of a changing industry.

What you will do

    • Work closely with data scientists, machine learning engineers, and clients to develop an understanding of the physics and engineering challenges being solved.
    • Set up and build multi-physics models to simulate and understand complex real-world phenomena.
    • Automate simulation pipelines to enable fast optimisation and parametric CAD coupling.
    • Use on-premise HPC and cloud resources to accelerate high-fidelity models beyond smart model setup and meshing choices.
    • Own the delivery of technical work streams, potentially mentoring more junior colleagues.
    • Work at the intersection of CAE and data science, generating highly accurate results and predictions in conjunction with advanced machine learning and deep learning models.
    • Continuously apply and improve engineering best practices and standards, coaching colleagues in their adoption.

What you bring to the table

    • Electromagnetic Modelling: Develop and analyse electromagnetic models, focusing on real-world applications such as antenna design, induction heating processes, wireless charging, electric motor technologies, and electronic shielding.
    • Create multi-physics simulations for electromagnetic, flow, thermal, and mechanical analyses to evaluate comprehensive system performance.
    • Possesses advanced knowledge in high-frequency and low-frequency electromagnetic simulation software (3-6 years), such as Ansys HFSS, COMSOL, Altair’s FEKO, Dassault CST, or other EM Simulation Tools.
    • Performance Optimisation: Identify and implement improvements based on simulation results to enhance system performance.
    • Demonstrate the ability to scope and effectively deliver projects.
    • Exhibit strong problem-solving abilities to analyse issues, identify causes, and recommend solutions quickly.
    • Collaboration and Communication: Possess excellent collaboration and communication skills to work effectively with teams and customers.
    • For more experienced candidates, have a passion for and a track record of managing, mentoring, and coaching junior colleagues.
    • Ideally, possess advanced Python and Java coding skills

What we offer

    • Be part of something larger: Make an impact and meaningfully shape an early-stage company. Work on some of the most exciting and important topics there are. Do something you can be proud of!
    • Work with a fun group of colleagues that support you, challenge you and help you grow. We come from many different backgrounds, but what we have in common is the desire to operate at the very top of our fields and solve truly challenging problems in science and engineering. If you are similarly capable, caring and driven, you'll find yourself at home here.
    • Experience a truly flat hierarchy. Voicing your ideas is not only welcome but encouraged, especially when they challenge the status quo.
    • Work sustainably, striking the right balance between work and personal life. Be able to properly switch off in the evening and during weekends. What matters is the quality of our work.
    • Receive a competitive compensation and equity package, in addition to plenty of perks such as generous vacation and parental leave, complimentary office food, as well as fun outings and events.
    • Work in a flexible setting, with the opportunity to collaborate in our lovely Shoreditch office and enjoy a good proportion of time working from home, if desired. Get the opportunity to occasionally visit our customers' engineering sites and experience first-hand how our work is transforming their ways of working.
    • Use first-class equipment for working in-office or remotely, including HPC.
We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.