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.

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

What you will do

Work closely with a multi-disciplinary team ranging form computational chemists with varied domain expertise to machine learning engineers to employ and advance the state-of-the-art machine learning techniques for solving a variety of problems in materials.
Develop and apply machine learning interatomic potentials (MLIPs) to model atomistic systems, leveraging and extending state-of-the-art frameworks and benchmark datasets.
Design and run experiments on large-scale chemistry and materials datasets, iterating on model architectures to improve accuracy, transferability, and generalisation across systems.
Own research workstreams at different levels of scope, depending on seniority, from model development through to evaluation on real-world materials problems.
Collaborate with the broader research team to ensure your models are robust, reproducible, and translatable into production-ready pipelines.
Work on high-performance computing infrastructure to handle the scale and complexity of atomistic simulations and generative modelling tasks.
Communicate your work internally and externally — through paper publications, industry workshops, and customer conversations — tailoring the message for both academic and non-academic audiences.
Mentor colleagues with less experience in computational chemistry or materials ML as the team grows.

What you bring to the table

Enthusiasm for applying machine learning to real-world materials science and computational chemistry challenges, with a genuine interest in seeing your research have industry impact.
Ability to scope and effectively deliver research projects, balancing rigour with pragmatism.
Strong problem-solving skills and the ability to move quickly from a materials or chemistry challenge to a tractable computational formulation.
Excellent collaboration and communication skills — with research colleagues, engineers, and customers alike.
PhD in computational chemistry, physics, materials science or a closely related field.
Hands-on experience in using and fine-tuning at least one MLIP backend such as MACE or FAIRChem/OCP and their integration into larger computational framework.
Direct experience with established chemistry and materials benchmark datasets, such as OC20, OC22, or the Materials Project.
Proficiency in Python and experience working in high-performance computing environments as well as experience in contributing towards a large multi-module codebase
Experience with generative models preferably applied to molecular or materials systems.

What we offer

Build what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.

Sustainable pace, long-term ambition

Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.

And it doesn’t stop there …

🚀 Equity options - share meaningfully in the company you’re helping to build.

🏦 10% employer pension contribution - because investing in future matters.

🍽️ Free office lunches - to keep you energised and focused.

👶 Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.

🍼 YellowNest nursery scheme - to help working parents manage childcare costs.

☀️ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.

🏥 Private medical insurance - 100% employee cover, giving you complete peace of mind.

💪 Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing.

👀 Eye tests - because good work depends on good health.

📈 Personal development - dedicated support for learning, development, and leveling up over time.

💛 Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it.

🚲 Bike2Work scheme and 🚆 Season ticket loan - to make getting to work easier and greener.

🚗 Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric.

🔎 Watch this space, we’re continuing to build this as we grow…

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.