Computational Physics Expert — AI Evaluation

About OpenTrain

OpenTrain is the #1 platform for people building careers in AI training and data labeling. We help skilled contributors find projects, build a unified portfolio, and grow a durable freelance career teaching AI systems by contributing high-quality annotations, evaluations, and domain expertise. Creating an OpenTrain account is free.

About AI training and why it matters

AI training (also called data labeling or human feedback work) is the human side of building modern AI. Specialists provide the examples, corrections, and evaluations that teach models to reason, interpret scientific data, and produce reliable outputs.

This work is often remote and flexible, accessible without prior industry placement, and offers a way to apply scientific skills directly to shape how state-of-the-art AI systems behave.

• Work remotely and often set flexible hours around other commitments.
• Contribute directly to how models learn scientific reasoning and data interpretation.

The role

OpenTrain is recruiting a Computational Physics Expert to contribute high-quality insights to AI evaluation projects for the client OpenTrain. You will apply computational and experimental physics expertise to evaluate model outputs, improve scientific benchmarks, and help shape evaluation protocols.

• Engagement: Contractor, part-time (freelance).
• Time requirement: 20+ hours per week.
• Location: Remote, worldwide; work language: English.
• Pay: Hourly, USD $20–$60/hr (PAY_PER_HOUR).
• Data & tasks: Document-based evaluation with EVALUATION_RATING label types;

What you'll do

You will use domain knowledge in computational physics to analyze scientific inputs, evaluate model outputs, and create clear, reproducible evaluation artifacts. Collaboration with interdisciplinary teams will be part of the work to ensure evaluation tasks reflect real scientific practice.

• Analyze, interpret, and synthesize large scientific datasets and experimental results.
• Develop, review, and refine quantitative models, simulations, or physics workflows for evaluation.
• Apply advanced numerical methods, Monte Carlo techniques, and HPC-aware approaches to evaluation tasks.
• Provide evaluation ratings and structured feedback on document-based model outputs.
• Document findings, write clear rationale for ratings, and communicate complex concepts to non-specialists.

Requirements

Candidates must meet the core technical and professional requirements below. These are firm criteria for participation in this evaluation work.

• PhD in physics or a closely related field, or equivalent industry/research experience.
• Expertise in computational physics, scientific computing, or simulation-heavy research.
• Proficiency with Python, C++, MATLAB, and scientific tools such as ROOT.
• Experience with numerical simulations, Monte Carlo methods, and HPC workflows.
• Strong analytical, quantitative, and mathematical reasoning abilities.
• Demonstrated experience in experimental or scientific data analysis.
• Excellent written and verbal communication skills in English.

Helpful background (not required)

The following backgrounds make a candidate especially competitive but are not strict requirements.

• Experience in particle physics, astrophysics, plasma/fusion, or quantum systems.
• Familiarity with AI/ML workflows, scientific benchmarking, or model evaluation practices.
• Track record of published research or contributions to scientific literature.

How the engagement works

Apply through OpenTrain by creating a free profile and submitting your interest for this project. Typical onboarding includes a short qualification or example task and project-specific instructions so you can begin contributing reliably.

As a contractor you will receive assignments that match your availability and expertise. Work is remote and flexible; compensation is hourly as stated. OpenTrain helps you build a portfolio of evaluation work and discover more projects as you gain experience.

• Application steps: create OpenTrain profile, apply to the posting, complete qualification tasks if requested.
• This is a contract, part-time engagement with ongoing hourly assignments; scheduling and volume depend on project needs.