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Internship Ai Training For Physics Jobs (NOW HIRING)

Mercor

Physics Researcher - AI Systems

New York, NY · On-site +1

$125 - $225/hr

Doctoral or postdoctoral training at a top-20 global institution for physics or STEM. * Competitive ... AI interview based on your resume * Submit form Resources & Support * For details about the ...

UniversalAGI

AI Product Engineer

San Francisco, CA · On-site

San Francisco | Work Directly with CEO & founding team | Report to CEO | OpenAI for Physics | 5 Days Onsite AI Product Engineer Location: Onsite in San Francisco Compensation: Competitive Salary ...

Weekday AI

Physics AI Trainer (PhD)

$70 - $85/hr

This role for one of Weekday's clients. We are currently helping hire for one of the leading AI ... PhD in Physics from a top tier university Work experience : 2+ years of academic experience ...

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Internship Ai Training For Physics information

What is the difference between Internship Ai Training For Physics vs Physics Research Assistant?

AspectInternship Ai Training For PhysicsPhysics Research Assistant
Required CredentialsEnrolled in or recent graduate of physics or related fieldBachelor's or Master's in Physics or related field
Work EnvironmentTraining programs, labs, collaborative projectsResearch labs, academic institutions, universities
Employer & Industry UsageTech companies, research institutions, startupsUniversities, government labs, research organizations
Common Search & Comparison IntentLearning AI applications in physics, entry-level trainingAssisting in physics research, academic projects

Internship Ai Training For Physics focuses on providing hands-on AI training tailored for physics applications, often for students or recent graduates. In contrast, a Physics Research Assistant supports ongoing research projects, typically requiring more specialized academic credentials. Both roles are integral to scientific advancement but differ in their focus—training versus active research participation.

What types of projects or tasks can I expect to work on during an AI Training Internship for Physics?

As an intern in AI training for physics, you'll typically assist with data preparation, model training, and validation tasks. You may work on projects such as developing machine learning models to analyze experimental or simulation data, automating data labeling, or building tools to interpret physical phenomena using AI. Collaboration with researchers, data scientists, and other interns is common, and you'll likely participate in team meetings to discuss findings and troubleshoot challenges. This hands-on experience provides exposure to both advanced physics concepts and practical AI techniques.

What is an Internship AI Training for Physics?

An Internship AI Training for Physics is a specialized program where students or recent graduates gain hands-on experience applying artificial intelligence (AI) techniques to problems in physics. Interns typically work on projects that involve data analysis, machine learning, or simulation, collaborating with researchers or industry professionals. The goal is to provide practical skills in both AI and physics, helping interns understand how automation and computational methods can advance scientific discovery. Such internships often include mentorship, exposure to cutting-edge research, and opportunities to contribute to real-world projects. They serve as a strong foundation for future careers in AI, physics, or related fields.

What are the key skills and qualifications needed to thrive as an Internship AI Training for Physics, and why are they important?

To thrive in an Internship focusing on AI Training for Physics, a solid understanding of physics concepts, programming (often Python), and basic machine learning principles is essential, typically supported by ongoing or completed coursework in related fields. Familiarity with tools such as TensorFlow, PyTorch, Jupyter Notebooks, and version control systems like Git is commonly required. Strong analytical thinking, problem-solving skills, and the ability to communicate technical ideas clearly help candidates stand out. These skills enable interns to effectively contribute to complex AI projects in physics, bridge theory with practical application, and collaborate within multidisciplinary teams.
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Internship Ai Training For Physics jobs near you
Infographic showing various Internship Ai Training For Physics job openings in the United States as of July 2026, with employment types broken down into 27% Internship, 46% Full Time, 20% Part Time, and 7% Temporary. Highlights an 67% In-person, and 33% Remote job distribution.

Physics Subject Matter Expert (AI Training)

Weekday AI

Remote

Contractor

Posted 24 days ago

Job description

This role is for one of our clients
$20 - $40/hourpay
Role Title: Physics Subject Matter Expert (AI Training)
Role Type: Contractor
Location: Remote
We are seeking a Physics Subject Matter Expert to contribute to the development of next-generation AI systems by applying deep expertise in physics. In this role, you will evaluate scientific content, develop high-quality technical materials, and help improve AI models through accurate, well-structured, and domain-specific input. Prior experience in AI is not required-your knowledge of physics and scientific reasoning is the key qualification.
Requirements
Key Responsibilities
Scientific Content Review
  • Evaluate and annotate scientific data, equations, and experimental findings across various physics disciplines.
  • Review technical content for scientific accuracy, clarity, completeness, and logical consistency.
  • Provide expert feedback to improve the quality of physics-related content used in AI training.
Content Development
  • Create and review problem sets, technical explanations, research summaries, and analytical write-ups covering both foundational and advanced physics concepts.
  • Develop clear, well-structured documentation that enables AI models to better understand scientific principles and reasoning.
  • Author or edit experimental descriptions and technical reports with precision and attention to detail.
AI Model Evaluation
  • Assess AI-generated responses for technical correctness, logical reasoning, and scientific rigor.
  • Identify inaccuracies, ambiguities, or gaps in AI-generated physics content and provide actionable recommendations for improvement.
  • Contribute to the creation and refinement of high-quality datasets used for AI training and benchmarking.
Collaboration & Continuous Improvement
  • Work collaboratively with project managers and subject matter experts in a remote environment.
  • Identify opportunities to improve data quality, content coverage, and evaluation methodologies.
  • Ensure timely delivery of high-quality work aligned with project milestones and quality standards.
Required Skills & Qualifications
  • Bachelor's, Master's, or PhD in Physics or a closely related field.
  • Strong understanding of Classical Mechanics, Electromagnetism, Thermodynamics, Quantum Mechanics, Modern Physics, and related concepts.
  • Experience writing research papers, technical reports, experimental documentation, or scientific publications.
  • Excellent analytical, problem-solving, and critical thinking abilities.
  • Strong written and verbal communication skills with the ability to explain complex scientific concepts clearly.
  • Ability to work independently and effectively in a remote, collaborative environment.
Preferred Qualifications
  • Experience with data analysis, computational physics, experimental design, or scientific modeling.
  • Ability to communicate complex physics concepts to both technical and non-technical audiences.
  • Experience reviewing scientific literature, technical documentation, or research publications.
  • Familiarity with collaborative research environments and remote project execution.
  • Passion for scientific research, education, and advancing AI through domain expertise.
Must-Have Skills
  • Physics
  • Scientific Research
  • Technical Writing
  • Data Analysis
  • Problem Solving
Good-to-Have Skills
  • Computational Physics
  • Experimental Design
  • Research Publications
  • Scientific Documentation
  • Mathematical Modeling
  • Analytical Thinking
  • Technical Review
  • Remote Collaboration

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