Physics Professor for AI Model Training [Remote]

Provide high-level domain guidance in high energy and mathematical physics to inform the training and evaluation of next-generation AI systems. This remote contractor role asks senior researchers to adjudicate contested physics arguments, compare alternative approaches, and produce defensible written judgments that senior physicists can review. No prior AI experience is required; your subject-matter expertise and research leadership are the primary qualifications.

• Adjudicate and render expert judgment on contested or competing physics arguments, solutions, or interpretations within your subfield.
• Compare alternative approaches to the same problem, specifying which approach is superior, under which assumptions, and in which parameter regimes.
• Identify and articulate meta-level criteria for evaluating robustness and validity, including key assumptions and breaking points of approximations.
• Provide calibrated confidence in assessments, clearly signaling when uncertainty or open questions remain.
• Draft defensible written evaluations suitable for review by fellow senior physicists, ensuring clarity and rigor.
• Use technical tools such as LaTeX, SymPy, Python, and Jupyter to verify or contrast technical claims as needed, and state when a question is unresolved in the field while listing the relevant considerations.

• Required skills: deep physics mastery in high energy or mathematical physics, expert judgment in ambiguous cases, meta-level reasoning, research leadership, and the ability to produce defensible written articulation.
• PhD in physics with demonstrated expertise and scholarly impact in the target 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 using one or more of these methods: AdS/CFT, on shell gravitational action, Weyl Fefferman Graham gauge, and/or tensor algebra of boundary curvature invariants.
• 3 to 5 recent representative publications in your target subfield, with arXiv identifiers or DOI references.
• Prior experience supervising PhD students or postdocs, or equivalent leadership in industry research settings.
• Proficiency with LaTeX, SymPy, Python, and Jupyter, and the willingness to indicate any gaps in experience with these tools.
• Exceptional written communication skills, able to articulate nuanced and well-reasoned judgments for a senior-audience review.

• Engagement type: Independent contractor.
• Location: Remote.
• Work will consist of providing high-level domain guidance on a customer project to help train and evaluate AI systems.
• No prior experience in AI is required; the role relies on domain expertise and research judgment.

Hourly pay range: $80.00 to $160.00 per hour.

• Candidates must be able to engage as independent contractors and receive hourly payment under contractor terms.

If interested, prepare a CV, 3 to 5 representative publications with arXiv or DOI references, and a brief note on your familiarity with LaTeX, SymPy, Python, and Jupyter including any gaps. Submitting these materials will enable evaluation of fit for the project.