Principal Research Scientist: CS / Computational Physics

You will help improve AI systems by applying deep research expertise in computer science and computational physics. The work focuses on open problems, proofs, algorithms, numerical experiments, simulations, and high-performance computing.

You will guide AI models and agents through multi-step research, test whether their results are correct and reproducible, and assess the novelty and importance of their work against current research. You will also write research memos and advise on promising research directions.

• Identify and clearly define open problems, theoretical limits, or simulation challenges where progress can be checked.
• Guide AI models and agents through proofs, algorithms, numerical experiments, and high-performance simulations.
• Check results through proof checks, computational reproduction, and formal methods.
• Evaluate and document the novelty, correctness, and significance of research outputs.
• Write concise memos covering research attempts, partial solutions, and model limitations or failure patterns.
• Recommend research areas and open problems that AI models and computational tools may be able to advance.

This is a part-time contractor role open to candidates in the countries listed below. The work requires a strong research record and the ability to assess technical work outside your immediate specialty.

• $100 to $400 per hour.
• Part-time contract work.
• Also open in Ghana, Greece, Indonesia, India, Italy, Jordan, Japan, Kenya, Kyrgyzstan, Kuwait, Kazakhstan, Lebanon, Sri Lanka, Morocco, Mexico, Malaysia, Nigeria, the Netherlands, Oman, Peru, and the Philippines.
• Also open in Pakistan, the Palestinian territories, Portugal, Qatar, Saudi Arabia, Singapore, Thailand, Tunisia, Taiwan, the United States, Uzbekistan, Vietnam, and South Africa.
• Professional fluency in English.
• Seven to ten or more years of active research in computer science or mathematical or computational physics.
• A strong record of scholarly contributions, including recent publications in leading venues.
• Field-level recognition, such as major prizes, society fellowships, or plenary or invited talks at leading scholarly events.
• Success resolving named open problems or introducing influential concepts adopted by peers.
• Hands-on experience with simulation, numerical analysis, algorithm implementation, or high-performance computing.
• Ability to rigorously examine technical work outside your immediate area of expertise.