Physics Research Auditor

About this role

Job Summary: 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.

Skills

Key responsibilities

• Conduct detailed technical reviews of advanced physics content, evaluating the accuracy and rigor of solutions across specialized subfields.
• Identify flaws, inconsistencies, and unsupported assumptions in research outputs and theoretical problem-solving approaches.
• Offer comprehensive feedback to clarify reasoning, highlight errors, and articulate corrective actions.
• Assess multiple solution methodologies with a broad yet deep theoretical perspective.
• Document findings clearly, communicating both in writing and verbally within the customer’s team environment.
• Contribute to the refinement of AI learning models by providing authoritative domain-specific judgments.
• Collaborate with a multidisciplinary group of experts, leveraging your peer review experience to ensure scientific integrity.

Required skills & qualifications

• PhD in physics or at least a senior PhD student with active research expertise in the assigned subfield (e.g., High Energy, Biophysics, Condensed Matter, AMO, Gravitation, Quantum Information, Optical Properties).
• Postdoctoral or junior professor standing in the relevant subfield preferred for auditor-level tasks.
• Publication of 2–5 peer-reviewed or arXiv/DOI-listed papers in the target area over the last five years.
• Demonstrated proficiency in LaTeX, SymPy, Python, and Jupyter (please flag any skills gaps).
• Exceptional written and verbal communication skills to explain complex scientific concepts and decisions.
• Experience in technical review, error detection, and evaluating scientific rigor and methodology.
• Eligibility to work in the US, UK, or Canada (stellar candidates outside these regions considered in rare cases).

Preferred qualifications

• Extensive hands-on experience with peer review or editorial work for scientific journals.
• Exposure to AI or data-driven research projects (not required but beneficial).
• Ability to sustain a commitment of approximately 10 hours per week over an 8–10 week period.
• Additional Info: This is an AI training initiative where your expertise directly influences the development of intelligent systems used in scientific research. You will play a pivotal role in setting the gold standard for research quality, data integrity, and theoretical depth, working remotely as part of our customer’s expert team.