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We are engaging Physics Experts, established Professors or Principal Investigators, to provide high-level domain guidance as part of an impactful project for are team. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required, your domain knowledge is what matters.
Job Responsibility
Adjudicate and render expert judgment on contested or competing physics arguments, solutions, or interpretations within your subfield
Compare alternative approaches to the same problem, detailing which is superior, under what assumptions, and in which regimes
Identify and articulate meta-level criteria for evaluating the robustness and validity of competing physics work, such as key assumptions and breaking points of approximations
Exercise calibrated confidence by providing authoritative assessments while transparently acknowledging genuine uncertainty or open questions in the field
Draft defensible written evaluations suitable for review by fellow senior physicists, ensuring clarity and rigor
Leverage technical tools such as LaTeX, SymPy, Python, and Jupyter to verify or contrast technical claims as needed
Clearly communicate when a question is unresolved within the field and delineate the pertinent considerations
Requirements
Physics mastery
Expert judgment in ambiguous cases
Meta-level reasoning
Research leadership
Defensible written articulation
PhD in physics with demonstrated expertise and scholarly impact in your specified subfield
Current or former Associate Professor, Full Professor, Chair Professor, or Principal Investigator/Group Leader with a track record of independent research leadership
Ongoing research activity in one or more of these areas: High Energy Physics, Mathematical Physics, Biophysics, Statistical Physics, Condensed Matter, AMO/Quantum Optics, Gravitation, Cosmology, Astrophysics, Quantum Information, or Optical Properties of Materials
3–5 recent representative publications in your target subfield, with arXiv or DOI references
Prior experience supervising PhD students or postdocs, or equivalent leadership in industry research settings
Proficiency with LaTeX, SymPy, Python, and Jupyter (please indicate any gaps in experience with these tools)
Exceptional written communication skills, with the ability to articulate nuanced and well-reasoned judgments