Quantum Research Scientist with Python - Freelance AI Trainer

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.

What This Opportunity Involves

Each project contains unique tasks. Contributors may:

• Design original computational physics problems that simulate real physics research workflows;
• Create problems requiring Python programming to solve (using Numpy, SciPy, Sympy);
• Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks);
• Develop problems requiring non-trivial reasoning chains in mechanics, electromagnetism, thermodynamics, and quantum mechanics;
• Base problems on real research challenges or practical applications from physics practice;
• Verify solutions using Python with standard physics simulation libraries;
• Document problem statements clearly and provide verified correct answers.

What We Look For

• Degree in Physics (Theoretical, Experimental, or Computational) or related fields;
• Python proficiency for numerical validation. MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent;
• 2+ years of professional experience: applied, research, or teaching experience is applicable;
• Experience with numerical simulation methods;
• Ability to design problems that mirror real physics research workflows;
• Creative thinking in problem design across diverse physics areas;
• Familiarity with physics modeling and approximation techniques;
• Strong written English (C1+).

Project Time Expectations

Estimated 10‑20 hours per week during active phases. This is not guaranteed and applies only while the project is active.

Compensation

On this project, contributors can earn up to $45 per hour equivalent , depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise.