PhD Residency - Scientific ML (SciML) and Multiscale Physics (Early Stage Project)
Mountain View, CA$100k - $157kinternshipPosted 1mo ago
About the role
2026/2027 PhD Residency focusing on Scientific Machine Learning and multiscale physics to accelerate materials discovery and manufacturing through physics-informed AI and advanced simulations. Location is Mountain View, CA at X's headquarters. Flexible 6 months to 1 year program with year-round rolling start dates. Paid internship with benefits and participation in AI/ML residency community.
Responsibilities
- Embed into one of X's confidential or public projects
- Contribute to building advanced simulations and models and custom equipment/processes for materials discovery and manufacturing
- Parameterize unresolved or complex physics into autodifferentiable physics solvers
- Implement, optimize, and scale SciML frameworks
- Work with laboratories and physical instrumentation environments
Qualifications
- 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), including parameterizing physics into autodifferentiable solvers and scaling relevant SciML frameworks
- Practical familiarity with laboratory environments, physical instrumentation, or demonstrated inclination to tinker and build
Skills
Required:PhD-level fundamentals in multiscale physicsScientific Machine Learning (SciML)Laboratory/instrumentation experience
Nice to have:PINNs / Neural Operators (preferred)High-performance simulation tools (e.g., COMSOL, OpenFOAM)Machine learning applied to complex physical systems
Benefits
- Paid compensation
- Benefits (as part of the internship program)
Last updated Oct 22, 2026. Interested? Apply on the company site.
About Google X
Welcome to X, Alphabet's Moonshot Factory. We create radical technologies to help solve some of the world’s hardest problems.
Welcome to X, Alphabet's Moonshot Factory. We create radical technologies to help solve some of the world’s hardest problems.
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