Remote Physics Research Scientist; PhD

Overview

We are seeking PhD-level Physics researchers to rigorously test the reasoning capabilities of large language models (LLMs). In this role, you’ll create physics problems, analyze model responses, and identify logical gaps to help improve AI’s conceptual understanding and structured problem-solving. This is a remote, contract-based role with flexible weekly hour options (10, 20, or 30).

Turing is hiring Physics Research Scientists (PhD, Remote) to test and improve how advanced AI models handle reasoning and problem-solving in physics. Work with top AI labs, contribute to frontier benchmarks, and earn upto $150/hr on a flexible, remote schedule.

• Design and evaluate challenging physics problems to test AI reasoning.
• Analyze AI-generated solutions for logic, rigor, and step-by-step clarity.
• Provide detailed, constructive feedback that highlights gaps in reasoning.
• Contribute to the development of benchmarks that measure model performance on abstract and multi-step tasks.
• Collaborate with researchers to refine methodologies for testing AI reasoning.

• PhD or Postdoctoral (or currently enrolled) in Physics, Applied Physics, or related fields.
• Strong ability to solve complex, multi-step problems with structured reasoning.
• Skilled communicator, able to explain logic and critique clearly in writing.
• Independent, self-motivated, and comfortable in a remote setting.
• Reliable computer and internet setup.

• Impact:
  Help define how AI models reason about abstract, scientific problems.
• Prestige:
  Work with leading AI labs shaping the future of reasoning systems.
• Flexibility:
  Remote-first, with weekly hour options.
• Career Growth:
  Gain experience at the intersection of AI and physics research.

• Compensation: $50–$150 per hour, based on skills and experience. (paid once every two weeks).
• Duration: 1 week to 3 months (project-based; extension possible).
• Hours: Up to 30 hrs/week.
• Time Zone: 2–5 hrs/day overlap with UTC-8 (America/), confirmed near onboarding.