2026/2027 PhD Residency - Scientific ML (SciML) and Multiscale Physics (Early Stage Project)

X, The Moonshot Factory is seeking a PhD resident to develop scientific machine learning models and advanced simulations for materials discovery and critical manufacturing challenges. The role combines fluid dynamics, multiscale physics, machine learning, experimentation, and custom equipment development to create efficient physics-informed simulation approaches.

What you'll do:

• Combining fluid dynamics and machine learning to solve some of the most important problems in materials discovery and manufacturing
• Working at the absolute forefront of simulation + experimentation, replacing computationally heavy, brute-force forward solvers with lean, physics-informed architectures
• To be embedded into one of our confidential or public X projects
• To get paid competitively and receive benefits
• To be a part of a lively community of AI and ML Residents
• To attend tech-talks with AI leaders from across X

What they're looking for:

• Must be actively enrolled in a PhD program
• First-principles understanding of multiscale physics from continuous fluid dynamics to discrete particle modeling
• Proven expertise in Scientific Machine Learning (SciML), specifically the ability to parameterize unresolved or complex physics (e.g., phase coupling, closure terms) into autodifferentiable physics solvers and implement, optimize, and scale relevant SciML frameworks
• Practical familiarity with laboratory environments, physical instrumentation, or a strong, demonstrated inclination to tinker and build
• Direct experience with PINNs, Neural Operators, and traditional ML
• Proficiency in high-performance simulation tools (e.g., COMSOL, OpenFOAM)
• Track record of applying machine learning to complex physical systems (e.g., turbulence, multiphase flow, or inverse design)

Benefits:

• Receive benefits
• To be a part of a lively community of AI and ML Residents
• To attend tech-talks with AI leaders from across X