Job Description

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. Key Responsibilities:

• Serve as the recognized adjudicator for advanced physics problems within your subfield, delivering authoritative scientific judgments.
• Evaluate and resolve conflicting methodologies, results, or interpretations submitted for AI training purposes.
• Review and refine scientific content for clarity, accuracy, and consistency, ensuring alignment with best research practices.
• Provide detailed written and verbal feedback to improve AI model understanding and outputs.
• Draw on a cross-disciplinary perspective to inform adjudication and highlight nuances or alternate approaches.
• Collaborate with a global team of experts, sharing insights to advance the quality of training datasets.
• Maintain high standards of scientific rigor in all assessments, reflecting leadership and mentorship experience in research environments.

• PhD in physics or senior PhD student (minimum), with ongoing research and publications in the relevant subfield.
• 2, 5 recent (past 5 years) representative publications available via arXiv/DOI.
• Demonstrated expertise as a professor, industry research PI, or equivalent subject matter authority.
• High-level scientific judgment for evaluating edge cases and resolving disagreements.
• Broad cross-disciplinary awareness and understanding of alternative research standards.
• Strong leadership background in mentoring, reviewing, or directing research projects/labs.
• Proficiency in LaTeX, SymPy, Python, and Jupyter (please flag any gaps).

• Experience adjudicating research disputes or peer-reviewing high-impact publications.
• Involvement in AI, machine learning, or computational modeling projects is a plus.
• Availability for a sustained commitment of approximately 10 hours per week over an 8, 10 week period.

Subfields of particular interest for this pilot include High Energy Physics/Mathematical Physics, Biophysics/Statistical Physics, Condensed Matter (including moiré systems, magnetic materials, PXP/Rydberg), AMO/Quantum Optics, Gravitation/Cosmology/Astrophysics, Quantum Information, and Optical Properties of Materials. Applicants should be based in the US, UK, or CA, though truly exceptional candidates from outside these locations may be considered. This is a unique opportunity to leverage your expertise within a pioneering AI training initiative as part of the customer''s team.

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