Research Scientist New York, United States

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. What you will do Work closely with our machine learning engineers, simulation engineers, and customers to translate physics and engineering challenges into mathematical problem formulations. Build models to predict the behaviour of physical systems using state‑of‑the‑art machine learning and deep learning techniques. Own research work‑streams at different levels, depending on seniority. Discuss results and implications of your work with colleagues and customers, especially how these results can address real‑world problems. Collaborate with colleagues beyond the research team to translate models into production‑ready code. Communicate your work to academic and non‑academic audiences – including paper publications, industry workshops, and customer conversations. Mentor junior colleagues in machine learning, data science, and statistics, fostering a nurturing environment. What you bring to the table Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering. Ability to scope and effectively deliver projects. Strong problem‑solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly. Excellent collaboration and communication skills – working with teams and customers alike. PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, or a related field, with particular expertise in one of the following: operator learning (neural operators) or other probabilistic methods for PDEs. geometric deep learning or other 3D computer vision methods for point‑cloud or mesh‑structured data. generative models for geometry and spatiotemporal data (VAEs, diffusion models, Bayesian non‑parametric, scaling to large datasets, etc.). Ideally, more than 2 years of experience in a data‑driven role, with exposure to: building machine learning models and pipelines in Python using common libraries and frameworks (NumPy, SciPy, Pandas, PyTorch, JAX). developing models for bespoke problem settings that involve high‑dimensional data (spatiotemporal, geometric, physical). iterating on network architectures and model structure, tuning and optimizing for inductive biases, improved generalisability, and performance. combining theoretical reasoning with empirical intuition to guide investigation. formulating and running experiment pipelines to benchmark models and produce comparable results. writing skills for communicating complex technical concepts to peers and non‑peers, tailoring the message for the required audience. Publication record in reputable venues that demonstrates mastery in your field, particularly in the domains above. Desirable venues include NeurIPS, ICML, ICLR, UAI, AISTATS, AAAI, Siggraph, CVPR, TPAMI, JMLR. What we offer Equity options – share in our success and growth. 5 % 401(k) match. Flexible working and hybrid setup with Manhattan office access and remote flexibility. Enhanced parental leave – 3 months full pay paternity and 6 months full pay maternity leave. Private health insurance – comprehensive coverage for you and your family. Personal development – access to learning and training. Gympass / Wellhub subsidised for you and up to 3 family members. Flexible Spending Account for eligible healthcare expenses. Free team lunch 1 × week. Salary range: $120,000 – 240,000, depending on experience. Seniority will be assessed throughout our interview process. Equality and diversity 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. Equal Opportunities Policy 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. #J-18808-Ljbffr PhysicsX Ltd