PhysicsX builds physics-based AI for industrial engineering that predicts physical behaviors quickly to accelerate design testing across industries.
<div class="content-intro"><h2>About us</h2> <div>PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.</div> <div>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.</div></div><h3><strong>Note: </strong>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.</h3> <h2><strong>What you will do </strong></h2> <ul> <li>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.</li> <li>Develop and apply machine learning interatomic potentials (MLIPs) to model atomistic systems, leveraging and extending state-of-the-art frameworks and benchmark datasets.</li> <li>Design and run experiments on large-scale chemistry and materials datasets, iterating on model architectures to improve accuracy, transferability, and generalisation across systems.</li> <li>Own research workstreams at different levels of scope, depending on seniority, from model development through to evaluation on real-world materials problems.</li> <li>Collaborate with the broader research team to ensure your models are robust, reproducible, and translatable into production-ready pipelines.</li> <li>Work on high-performance computing infrastructure to handle the scale and complexity of atomistic simulations and generative modelling tasks.</li> <li>Communicate your work internally and externally — through paper publications, industry workshops, and customer conversations — tailoring the message for both academic and non-academic audiences.</li> <li>Mentor colleagues with less experience in computational chemistry or materials ML as the team grows.</li> </ul> <p> </p> <h2><strong>What you bring to the table</strong></h2> <ul> <li>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.</li> <li>Ability to scope and effectively deliver research projects, balancing rigour with pragmatism.</li> <li>Strong problem-solving skills and the ability to move quickly from a materials or chemistry challenge to a tractable computational formulation.</li> <li>Excellent collaboration and communication skills — with research colleagues, engineers, and customers alike.</li> <li>PhD in computational chemistry, physics, materials science or a closely related field.</li> <li>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.</li> <li>Direct experience with established chemistry and materials benchmark datasets, such as OC20, OC22, or the Materials Project.</li> <li>Proficiency in Python and experience working in high-performance computing environments as well as experience in contributing towards a large multi-module codebase</li> <li>Experience with generative models preferably applied to molecular or materials systems.<br><br></li> </ul> <h2><strong>What we offer</strong></h2> <p><strong>Build what actually matters</strong></p> <p>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.</p> <p><strong>Learn alongside exceptional people</strong></p> <p>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.</p> <p><strong>Influence over hierarchy</strong></p> <p>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.</p> <p><strong>Sustainable pace, long-term ambition</strong></p> <p>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.</p> <p><strong>And it doesn’t stop there …</strong></p> <p>🚀 <strong>Equity options</strong> - share meaningfully in the company you’re helping to build.</p> <p>🏦 <strong>10% employer pension contribution</strong> - because investing in future matters.</p> <p>🍽️ <strong>Free office lunches</strong> - to keep you energised and focused.</p> <p>👶 <strong>Enhanced parental leave</strong> - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.</p> <p>🍼 <strong>YellowNest nursery scheme</strong> - to help working parents manage childcare costs.</p> <p><strong>☀️ 25 days of Annual Leave (+ Public Holidays)</strong><span class="Apple-converted-space"> </span>- because taking time to rest matters.</p> <p>🏥 <strong>Private medical insurance</strong