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Quantum Intern Jobs (NOW HIRING)

Crown Innovations, Inc.

NAMS-2 Intern

Mountain View, CA · On-site

You will contribute to initiatives spanning Air Traffic Management, Advanced Technology Systems, AI, LLM, Quantum Computing, Nanoelectronics and Devices, or Advanced Software. As an intern, you will ...

Crown Innovations, Inc.

NAMS-2 Intern

Mountain View, CA · On-site

$730/wk

You will contribute to initiatives spanning Air Traffic Management, Advanced Technology Systems, AI, LLM, Quantum Computing, Nanoelectronics and Devices, or Advanced Software. As an intern, you will ...

Barrow Wise Consulting

Internship

MD · On-site

$15/hr

What You'll Do: As an Intern, you will have the opportunity to: * Technical Writing & Editing ... Dive into the exciting world of Artificial Intelligence and Quantum Technology to keep us at the ...

Technergetics

R&D Engineering Intern

Rome, NY

$22 - $28/hr

Position: R&D Engineering Intern   Opportunity Overview: Technergetics is searching for a ... Quantum computing, machine learning and artificial intelligence, AI-enabled edge devices, and many ...

Jasper Builds

Social Media Intern

Nashville, TN · On-site

Salary: $18-$20 hour Social Media Intern, 2026 JASPER | Luxury Full-Home Renovation & Design-Build ... Jasper is proud to be recognized as a 2026 Quantum Certified Workplace in Nashville, reflecting our ...

The Pennsylvania State University

$14.75 - $19.75/hr

We are searching for an Undergraduate student to join the Quantum Research Department of the Communications, Information and Navigation Office (CINO) at the Applied Research Laboratory (ARL) at Penn ...

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Quantum Intern information

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How much do quantum intern jobs pay per hour?

As of Jul 7, 2026, the average hourly pay for quantum intern in the United States is $17.04, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What is the difference between Quantum Intern vs Quantum Research Assistant?

AspectQuantum InternQuantum Research Assistant
Required CredentialsEnrolled in or recent graduate of a related degree (e.g., physics, engineering)Typically holds or is pursuing a master's or PhD in a relevant field
Work EnvironmentInternship programs, often in corporate or research labsResearch labs, academic institutions, or industry research teams
Employer & Industry UsageTech companies, startups, research institutionsUniversities, government agencies, industry R&D
Common Search & ComparisonEntry-level, internship-focused rolesResearch-focused, more advanced position

The main difference between a Quantum Intern and a Quantum Research Assistant lies in experience level and responsibilities. Interns are typically students gaining initial exposure, while research assistants are more experienced, often holding advanced degrees, and involved in more complex research tasks.

What cities are hiring for Quantum Intern jobs? Cities with the most Quantum Intern job openings:
What are the most commonly searched types of Quantum jobs? The most popular types of Quantum jobs are:
What states have the most Quantum Intern jobs? States with the most job openings for Quantum Intern jobs include:
Quantum Intern jobs near you
Infographic showing various Quantum Intern job openings in the United States as of July 2026, with employment types broken down into 18% Internship, 1% As Needed, 50% Full Time, 28% Part Time, 2% Temporary, and 1% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $35,436 per year, or $17 per hour.

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Re-posted yesterday

Job description

Ph.D. Graduate Intern – Quantitative Portfolio Risk Analytics (Cross-Disciplinary)

Position Overview
We are seeking an exceptional Ph.D. graduate student to join our team as a Quantitative Portfolio Risk Analytics Intern. This role focuses on developing and applying advanced analytical methods to understand portfolio risk, market structure, and complex financial systems.
We are intentionally recruiting from cross-disciplinary, research-driven backgrounds. Doctoral candidates from fields such as physics, astrophysics, math, applied mathematics, statistics, engineering, economics, computer science, quantum computing, biotech, and other data-intensive sciences are strongly encouraged to apply—especially those interested in translating rigorous quantitative methods into real-world financial applications.
Key Responsibilities
  • Develop and enhance quantitative models for portfolio risk, including factor-based and statistical approaches 
  • Analyze large, high-dimensional financial datasets to uncover structure, dependencies, and sources of risk 
  • Design and implement analytical tools and pipelines using Python and SQL 
  • Contribute to model validation, backtesting, and performance evaluation 
  • Collaborate with risk, engineering, and data teams to improve model scalability and data infrastructure 
  • Communicate complex quantitative insights through clear visualizations and technical summaries 
  • Apply advanced methodologies from your discipline (e.g., stochastic modeling, optimization, machine learning, or geometric/topological approaches) to improve risk analytics 
Required Qualifications
  • Currently enrolled in a graduate Ph.D. program in a highly quantitative field (e.g., Math, Applied Mathematics, Physics, Astrophysics, Statistics, Computer Science, Engineering, Financial Engineering, Economics, Biotech or other data-driven disciplines) 
  • Strong foundation in probability, statistics, and numerical methods 
  • Proficiency in Python (NumPy, pandas, or similar) and/or SQL 
  • Experience working with large datasets and implementing quantitative models 
  • Ability to think rigorously about complex systems and translate theory into practical solutions 
Preferred Qualifications
  • Familiarity with quantitative finance concepts (e.g., portfolio theory, factor models, volatility modeling, Value-at-Risk) 
  • Experience with scientific computing, optimization, or machine learning 
  • Background or research in cross-disciplinary areas such as: 
    • Statistical physics, complex systems, or network theory 
    • Applied or computational mathematics 
    • Machine learning or probabilistic modeling 
    • Quantum computing or advanced optimization techniques 
    • Topological data analysis or geometric data methods 
  • Prior research, publications, or project work demonstrating advanced quantitative modeling 
What You’ll Gain
  • Exposure to real-world portfolio risk problems at the intersection of finance and advanced analytics 
  • Opportunity to apply cutting-edge academic methods in a production environment 
  • Collaboration with a highly quantitative, cross-disciplinary team 
  • Experience working with large-scale financial data and modern analytics infrastructure 
  • Mentorship and potential pathway to full-time quantitative roles 
Duration & Compensation
  • Internship: Summer 2026, with potential to extend 
  • Paid internship (competitive, based on experience and location)