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Freelance Quantum Research Scientist & AI Trainer (Python Expert)

MindriftRemote — Belo Horizonte, State of Minas Gerais, Brazil
Remote Part-time $14/hr - $14/hr

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Experience Level

Experience

Qualifications

This opportunity is ideal for quantum researchers with Python experience who are open to flexible, part-time, non-permanent engagements. The ideal candidates will possess:A degree in Physics (Theoretical, Experimental, or Computational) or related fields;Proficiency in Python for numerical validation; knowledge of MATLAB, R, C, SQL, Numpy, Pandas, SciPy, or any domain-specific libraries is equivalent;At least 2 years of professional experience, which can encompass applied, research, or teaching roles;Experience with numerical simulation techniques;The ability to design problems that reflect genuine physics research processes;Innovative thinking in problem creation across various physics domains;Familiarity with physics modeling and approximation methodologies;Excellent written English skills (C1+).

About the job

We invite you to submit your CV in English and specify your English proficiency level.

Mindrift is a dynamic platform connecting experts with project-based AI opportunities at leading tech firms, specializing in the testing, evaluation, and enhancement of AI systems. Please note that participation is project-based and does not constitute permanent employment.

About the Role:

Each project presents unique challenges, where contributors may:

  • Devise original computational physics challenges that emulate authentic physics research workflows;
  • Formulate problems necessitating Python programming solutions (utilizing libraries such as Numpy, SciPy, and Sympy);
  • Ensure problems are computationally demanding and cannot be manually resolved within a practical timeframe (days/weeks);
  • Create problems involving complex reasoning chains in mechanics, electromagnetism, thermodynamics, and quantum mechanics;
  • Base problems on genuine research issues or applicable scenarios from physics.
  • Validate solutions using Python alongside standard physics simulation libraries;
  • Clearly document problem statements and provide verified accurate answers.

Qualifications We Seek:

This opportunity is ideal for quantum researchers with Python experience who are open to flexible, part-time, non-permanent engagements. The ideal candidates will possess:

  • A degree in Physics (Theoretical, Experimental, or Computational) or related fields;
  • Proficiency in Python for numerical validation; knowledge of MATLAB, R, C, SQL, Numpy, Pandas, SciPy, or any domain-specific libraries is equivalent;
  • At least 2 years of professional experience, which can encompass applied, research, or teaching roles;
  • Experience with numerical simulation techniques;
  • The ability to design problems that reflect genuine physics research processes;
  • Innovative thinking in problem creation across various physics domains;
  • Familiarity with physics modeling and approximation methodologies;
  • Excellent written English skills (C1+).

How the Process Works:

Apply → Meet qualifications → Join a project → Complete assigned tasks → Get compensated.

Project Commitment:

For this engagement, tasks are estimated to require approximately 10-20 hours per week during active phases, contingent on project needs. This is merely an estimate and does not guarantee a fixed workload outside of active project phases.

Compensation:

Contributors can earn up to $14 per hour, depending on their contribution level and pace. Please note that compensation varies by project based on scope, complexity, and required expertise. Other projects available on the platform may offer varying compensation rates based on their specific requirements.

About Mindrift

Mindrift is a cutting-edge platform dedicated to connecting skilled professionals with innovative project-based AI opportunities in leading technology companies. We focus on enhancing AI systems through rigorous testing and evaluation, providing a unique avenue for experts to contribute to real-world challenges in artificial intelligence.

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