Principal Data Scientist

<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 &amp; 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&nbsp;</strong></h2> <ul> <li>Own Research work-streams at a high-level to deliver outcomes. <ul> <li>Align priorities with problem stakeholders, internal and external.</li> <li>Set the technical direction for the stream and apply judgement and taste to drive progress.</li> <li>Plan roadmaps with clear milestones for key decisions and outcomes.</li> <li>Organise and guide the more junior members of the team to effectively execute and deliver against this roadmap.</li> <li>Communicate purpose and key outcomes to raise awareness across the company and create opportunities for use and deployment.</li> </ul> </li> <li>Contribute towards Research group strategy and culture. <ul> <li>Identify research areas that would be valuable to the company and champion their development, ordering wrt other research objectives.</li> <li>Promote effective working patterns and proactively flag issues with team dynamics to foster a productive environment.</li> <li>Nurture younger colleagues to grow their skillset and guide their professional development.</li> </ul> </li> <li>The below activities in particular. <ul> <li>Work closely with our machine learning engineers, simulation engineers, and customers to translate physics and engineering challenges into mathematical problem formulations.</li> <li>Build models to predict the behaviour of physical systems using state-of-the-art machine learning and deep learning techniques.</li> <li>Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems.</li> <li>Collaborate with colleagues beyond the research team to translate your models into production-ready code.</li> <li>Communicate your work to others internally and externally as called for in paper publication venues, industry workshops, customer conversations, etc. This will involve writing for academic and non-academic audiences.</li> </ul> </li> </ul> <p>&nbsp;</p> <h2><strong>What you bring to the table</strong></h2> <ul> <li>Ability to scope and effectively deliver projects.</li> <li>Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering.</li> <li>Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.</li> <li>Excellent collaboration and communication skills — with teams and customers alike.</li> <li>PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, or a related field, with particular expertise in any of the following: <ol> <li>operator learning (neural operators), or other probabilistic methods for PDEs;</li> <li>geometric deep learning or other 3D computer vision methods for point-cloud or mesh-structured data;</li> <li>generative models for geometry and spatiotemporal data (VAEs, Diffusion Models, Bayesian non-parametric, scaling to large datasets, etc.).</li> </ol> </li> <li>Ideally, &gt;4 years of experience in a data-driven role in a <em><strong>professional industry</strong></em> setting, where you have been instrumental in: <ul> <li>building machine learning models and pipelines in Python, using common libraries and frameworks (PyTorch / CUDA, ideally with exposure to JAX, NumPy / SciPy), especially including deep learning applications;</li> <li>developing models for bespoke problem settings that involve high-dimensional data (spatiotemporal, geometric, physical);</li> <li>iterating on network architectures and model structure, tuning and optimising for inductive biases, improved generalisability, and improved performance;</li> <li>combining theoretical reasoning with empirical intuition to guide investigation;</li> <li>formulating and running experiment pipelines to benchmark models and produce comparable results;</li> <li>writing skills for communication complex technical concepts to peers and non-peers, tailoring the message for the required audience.</li> </ul> </li> <li>Publication record in reputable venues that demonstrates mastery in your field, and in particular the domains of interest listed above. Desirable venues include (but not limited to): NeurIPS, ICML, ICLR, UAI, AISTATS, AAAI, Siggraph, CVPR or TPAMI/JMLR.</li> </ul> <h2>&nbsp;</h2> <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&nbsp;- 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>🚀&nbsp;<strong>Equity options</strong>&nbsp;- share meaningfully in the company you’re helping to build.</p> <p>🏦&nbsp;<strong>10% employer pension contribution</strong>&nbsp;- because investing in future matters.</p> <p>🍽️&nbsp;<strong>Free office lunches</strong>&nbsp;- to keep you energised and focused.</p> <p>👶&nbsp;<strong>Enhanced parental leave</strong