Physics Expert

Opportunity Overview Handshake is looking for experienced computational and theoretical physicists to support AI research through flexible, part-time contract work. This is not a traditional job — you'll draw on your hands-on experience in numerical simulation, scientific computing, or your physics subfield to evaluate AI-generated content and provide feedback that helps AI reason like a practicing physicist. This is an ongoing, project-based opportunity you can take on alongside your current role. What You'll Do Use your domain expertise to create expert-level physics problems and scenarios grounded in real simulation, modeling, and computational workflowsReview and evaluate AI-generated responses for technical accuracy, numerical rigor, and alignment with how the work is actually doneProvide structured written feedback to help improve AI model performanceComplete tasks at your own pace with no set schedule or minimum hour requirement Qualifications Ideal candidates meet all three of the following: Industry/research experience — first-author publications in a computational subfield or 2+ years of hands-on industry experienceDegree — PhD in Physics, with a computational or theoretical focusSub-domain depth — demonstrated expertise in one of the following areas:Numerical simulation, PDE/ODE solvers, and Monte Carlo methodsHPC and scientific computing (NumPy/SciPy, C++/Fortran)A core subfield such as condensed matter, astrophysics, high-energy physics, or fluid dynamics Candidates who meet at least 2 of the 3 qualifications above are also encouraged to apply. Additional Qualifications (not Required, But Strengthen Your Application) Proficiency running large-scale simulations on HPC clusters across multiple scientific computing environmentsExperience with lattice methods or other specialized techniques within your subfield Required For All Applicants Must have US work authorizationStrong written communication and attention to detailAbility to explain complex physics concepts clearlyAbility to work independently in a remote, asynchronous environment #HandshakeAI