Research Scientist

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.

• 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 behavior 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 the 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 your models into production-ready code.
• 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.
• Foster a nurturing environment for colleagues with less experience in DS / ML / Stats for them to grow and you to mentor.

• 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 analyze issues, identify causes, and recommend solutions quickly.
• Excellent collaboration and communication skills — with teams and customers alike.
• PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, or a related field, with particular expertise in any 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, >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 (e.g., Num Py, Sci Py, Pandas, PyTorch, JAX), especially including deep learning applications;
• 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 generalizability, and improved 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 communication 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, 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.

• Equity options – share in our success and growth.
• 5% 401(k) match – invest in your future.
• Flexible working – balance your work and life in a way that works for you.
• Hybrid setup – enjoy our Manhattan office while keeping remote flexibility.
• Enhanced parental leave – support for life's biggest milestones.
• Private healthcare – comprehensive coverage for you and your family.
• Personal development – access learning and training to help you grow.
• Work from anywhere – extend your remote setup to enjoy…