Research Physicist With Python Experience - Freelance Ai Trainer - Up To $29 An Hour - Remote
Please submit your CV in English and indicate your level of English proficiency.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
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 proficiencyfor 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 professionalexperience: 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 physicsmodeling and approximation techniques;
Strong written English (C1+).
How It WorksApply → Pass qualification(s) → Join a project → Complete tasks → Get paid.Project Time ExpectationsFor this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.CompensationOn this project, contributors can earn up to $29 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise.#J-18808-Ljbffr
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 proficiencyfor 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 professionalexperience: 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 physicsmodeling and approximation techniques;
Strong written English (C1+).
How It WorksApply → Pass qualification(s) → Join a project → Complete tasks → Get paid.Project Time ExpectationsFor this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.CompensationOn this project, contributors can earn up to $29 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise.#J-18808-Ljbffr