Compensation: $80–$100/hr
Location: Remote
Employment Type: Contract
In this role, you'll leverage your advanced physics expertise to contribute to the training of next-generation AI systems. Your insights will play a crucial role in shaping how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required; your domain knowledge is what truly matters.
Utilize your advanced physics expertise to solve complex, novel problems and provide high-quality input for AI model training.
Review, analyze, and annotate research materials or data in your specialized subfield.
Document your thought processes and solutions clearly using LaTeX, Jupyter, and Python to ensure reproducibility and clarity.
Collaborate with the customer's team to refine problem statements and deliver detailed feedback on model outputs.
Engage in rigorous research and literature review to ensure the accuracy and relevance of data provided to the AI.
Communicate findings and insights effectively, both in writing and verbally, to technical and non-technical stakeholders.
Maintain confidentiality and uphold data integrity throughout the AI training process.
PhD in Physics or currently a senior-level PhD student with research focus in one or more of the specified subfields.
Active research record with 2–5 representative publications (within the last ~5 years), with arXiv or DOI references.
Proficiency in LaTeX, SymPy, Python, and Jupyter for technical communication and computational work.
Demonstrated strong written and verbal communication skills, with a focus on clarity and precision.
Proven expertise in at least one of the following subfields: High Energy Physics/Mathematical Physics, Biophysics/Statistical Physics, Condensed Matter (moiré systems, magnetic materials, PXP/Rydberg), AMO/Quantum Optics, Gravitation/Cosmology/Astrophysics, Quantum Information (error correction, spin squeezing, f-divergences, Haar measures), Optical Properties of Materials.
Postdoctoral experience or equivalent industrial research background.
Experience with interdisciplinary research or collaborative scientific teams.
Familiarity with AI, machine learning, or data science concepts (not required, but advantageous).
Individuals with a passion for research, detail-oriented problem-solving, and a drive to shape the future of AI are strongly encouraged to apply. Your insights and technical acumen will directly influence the development of advanced AI models in real-world contexts.
