Physics Expert - AI Training Project (India)

What You'll Do6

• Build expert-level physics problems and scenarios that mirror real simulation, modeling, and computational workflows.
• Review AI-generated responses for technical accuracy, numerical rigor, and fidelity to how physicists work in practice.
• Write structured feedback that helps AI models improve their reasoning in your domain.
• Apply subfield depth in areas such as condensed matter, astrophysics, high-energy physics, or fluid dynamics.
• Use PDE/ODE solvers, Monte Carlo methods, or HPC practices when you assess model output.
• Work at your own pace with no fixed schedule or minimum hour target.

Requirements11

• Indian work authorization.
• PhD in Physics with a computational or theoretical focus.
• First-author publications in a computational subfield or 2+ years of hands-on industry experience.
• Demonstrated depth in numerical simulation, PDE/ODE solvers, or Monte Carlo methods.
• HPC and scientific computing experience with tools such as NumPy, SciPy, C++, or Fortran.
• Expertise in a core subfield like condensed matter, astrophysics, high-energy physics, or fluid dynamics.
• Clear written explanations of complex physics concepts.
• Independent work in a remote, asynchronous setting.
• Strong attention to detail.
• Bonus: running large-scale simulations on HPC clusters across multiple scientific computing environments.
• Bonus: lattice methods or other specialized techniques in your subfield.

Who Should Apply

Physicists who hold a PhD with a computational or theoretical focus and can point to first-author papers or at least two years of industry work will fit this project. You should also bring real depth in one area such as numerical simulation, Monte Carlo methods, HPC, condensed matter, astrophysics, high-energy physics, or fluid dynamics. The role suits someone who writes clear explanations of complex physics and can work alone on an asynchronous schedule. Candidates without Indian work authorization will not move forward, and applicants who treat this as a full-time job or lack written communication examples often score low. A common rejection reason is a profile that lists physics knowledge but shows no concrete simulation, solver, or HPC work.

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