- Location
- New York · New York, New York, United States
- Department
- Delivery
- Seniority
- Senior
- Education
- PhD
- Source
- Greenhouse
Description
About us
PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.
We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.
Who We’re Looking For
We are seeking a skilled Electromagnetic Simulation Expert with a strong focus on high-frequency electromagnetics applications in the semiconductor domain including chip and advanced package design, signal and power integrity, high-speed interconnects, and EMI/EMC. Experience with adjacent applications such as antenna design, induction heating, or electric motors is also valuable.
You bring deep expertise in electromagnetic theory and simulation, with demonstrated hands-on experience in one or more key areas: low-frequency electromagnetics, including magnetostatics, electrostatics, motors, transformers, actuators, and eddy current analysis; high-frequency electromagnetics, spanning microwave components, antennas, radar and RCS modeling, S-parameter analysis, and signal and power integrity; or EMI/EMC analysis across the frequency spectrum.
You have a solid ability to apply fundamental knowledge to real-world phenomena across automotive and electric vehicles, aerospace and defense, telecommunications, semiconductor and electronics, and other industries. Highly proficient in at least one industry-standard EM simulation platform, you are adept at using these tools to create efficient, scalable workflows that drive impactful results. Relevant tools in this space include Ansys HFSS, Ansys Maxwell, CST Studio Suite, COMSOL Multiphysics with its RF and AC/DC modules, Altair FEKO, Altair Flux, and Siemens Simcenter MAGNET. Coding skills in Python and/or MATLAB, or the ability to quickly learn programming languages, is an advantage. Experience with PCB layout and signal integrity analysis using tools such as Cadence Allegro, Altium Designer, or Ansys SIwave is a nice to have.
With at least 3 to 5 years of industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready to hit the ground running. You're comfortable setting up complex EM simulations independently, interpreting results with depth, and making informed decisions based on solid physics and engineering judgement.
As a Senior Simulation Engineer, you won't just create models, you'll build what truly matters.
This Role
In this role, you'll work closely with our Data Scientists, Machine Learning Engineers, and customers to understand and define the electromagnetics engineering challenges we are solving. You'll play a crucial role in delivering high-fidelity simulations by:
- Independently building complex electromagnetic models from the ground up, covering low-frequency and high-frequency EM applications, to simulate and understand complex real-world phenomena, including using experimental data to validate simulations and ensure accuracy.
- Automating simulation pipelines, enabling fast optimization and parametric design coupling for efficient results across a broad range of EM applications.
- Leveraging our cloud platform and on-premises HPC to accelerate high-fidelity models beyond smart model setup and meshing choices.
- Collaborating closely with customers to understand their engineering challenges and solve them using simulation and AI. You will present results clearly and suggest next steps while balancing accuracy and efficiency, often working under pressure to meet tight deadlines.
- Working at the intersection of CAE and data science, generating accurate simulation results and predictions to train advanced Machine Learning and Deep Learning models.
- Continuously improving engineering practices, adapting EM model setups and outputs to support the development of Deep Learning surrogates.
- Mentoring junior engineers as part of a collaborative team.
- Traveling to customer sites in the North America area, an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on site.
As the role evolves, there are exciting opportunities for growth as an individual contributor or a technical lead, especially if you’re driven to take ownership of more complex projects and lead the direction of future solutions.
Please note, this role is based in New York City, working 2-3 days per week in our new office.
Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you’ll contribute to this exciting journey!
Please note, this role is based in New York City, working 2-3 days per week in our new office.
Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you’ll contribute to this exciting journey!
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.
We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.
Skills
PythonMATLABMachine LearningDeep LearningData ScienceCompliance
