<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 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>Own Research work-streams at different levels, depending on seniority.</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> <li>Foster a nurturing environment for colleagues with less experience in DS / ML / Stats for them to grow and you to mentor.</li> </ul> <p> </p> <h2><strong>What you bring to the table</strong></h2> <ul> <li>Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering.</li> <li>Ability to scope and effectively deliver projects.</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>ope