Physics Research Review Expert for AI Training
Join OpenTrain as a remote Physics Research Review Expert to solve advanced physics problems, annotate research documents, and provide detailed technical feedback used to train AI. This contractor role requires a PhD (or senior PhD student), 20+ hrs/week, and pays $80–$100/hr.
Generative Ai Rlhf
$80–$100/hr
Compensation
Worldwide
Eligibility
Entry
Experience
Jun 29, 2026
Posted
Open worldwide
About OpenTrain
OpenTrain is the #1 platform for people building careers in AI training and data labeling. We help contributors discover projects, build a unified AI-training portfolio, and grow into durable freelance careers in a fast-growing industry. Creating an OpenTrain account is free.
Why AI training matters
AI models learn from human-provided examples, and high-quality subject-matter contributions are essential to making them accurate and reliable. Work in AI training is remote, flexible, and places contributors on the cutting edge of how state-of-the-art systems behave.
The role
We are recruiting a remote Physics Research Review Expert (contract, part-time) to help train next-generation AI systems for OpenTrain. This role centers on advanced physics problem solving, annotation and review of research documents, and detailed technical feedback that improves model outputs.
Commitment: 20+ hours/week. Location: worldwide (remote). Language: English. Employment type: contractor, part-time. Data type: documents. Labeling tasks include classification and entity/NER classification; the project uses a custom (OTHER) annotation tool.
What you'll do
- Solve complex, novel physics problems and provide worked solutions suitable for model training.
- Review, analyze, and annotate research materials or data in a specialized physics subfield (document-level annotation).
- Document reasoning and solutions clearly using LaTeX, Jupyter, Python, and SymPy.
- Provide detailed feedback to improve model outputs and collaborate with the project team to refine problem statements.
- Conduct rigorous literature reviews to support the accuracy and relevance of provided data.
- Communicate findings clearly in writing and verbally with technical and non-technical stakeholders.
- Maintain confidentiality and data integrity throughout the training process.
Requirements
- PhD in Physics, or a senior-level PhD student actively engaged in research in a relevant subfield.
- Active research record with roughly 2–5 representative publications from the last ~5 years.
- Proficiency with LaTeX, SymPy, Python, and Jupyter for documenting and demonstrating solutions.
- Strong written and verbal communication skills; able to explain advanced methods clearly.
- Expertise in at least one relevant subfield such as High Energy Physics, Mathematical Physics, Biophysics, Statistical Physics, Condensed Matter, AMO, Quantum Optics, Gravitation, Cosmology, Astrophysics, Quantum Information, or Optical Properties of Materials.
- Ability to maintain confidentiality and ensure data integrity in all deliverables.
Helpful background
- Postdoctoral experience or equivalent industrial research background.
- Interdisciplinary research experience or history of working on collaborative scientific teams.
- Familiarity with AI, machine learning, or data science concepts (useful but not required).
Compensation and how it works
Pay: hourly, USD $80–$100 per hour (paid per hour). This is a contractor role; hours and cadence are agreed with the project team but expect 20+ hours/week.
How to apply: Create or use your OpenTrain profile to apply, attach your CV and 2–5 representative publications (preferably from the last five years), and include examples of LaTeX/Jupyter work if available. The project is open to applicants worldwide; English fluency is required.