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

InternshipMountain View, CA

How you will make 10x impact:

  • Combining fluid dynamics and machine learning to solve some of the most important problems in materials discovery and manufacturing
  • Work at the absolute forefront of simulation + experimentation, replacing computationally heavy, brute-force forward solvers with lean, physics-informed architectures

This project aims to push the limits of science and modeling as we know them and to prove how ML can radically accelerate our understanding of the world

  • Location: X's headquarters in Mountain View, CA
  • Start Date(s): Year-round rolling basis
  • Duration: a flexible 6 mo. to 1 year program based on project team needs and your availability

Throughout your AI Residency you can expect:

  • 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 you should have:

  • 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

It’d be great if you also had these:

  • 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)

Additional public information:

The US base salary range for this position is $100,000 - $157,000 + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include benefits.

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