Masters Intern - Quantum Computing at Pacific Northwest National Laboratory

Wayne State University; New York (NY); Hybrid; USD 25,000 - 35,000; Full time

Job summary

A research laboratory is seeking highly motivated Master's interns for 2026 to contribute to impactful research in quantum computing. Interns will engage with cutting-edge projects, collaborate with leading scientists, and present their findings in weekly meetings. Candidates must be currently enrolled in a Master's program and have a minimum GPA of 3.0, with preferred qualifications including familiarity with quantum error correction, machine learning methods, and various quantum technologies.

Qualifications

• Candidates must be enrolled in a Master's program.
• Minimum GPA of 3.0 is required.

Responsibilities

• Contribute and research a variety of topics with staff scientists.
• Present research progress in weekly team meetings.
• Engage with interns and scientists to develop quantum capabilities.

Skills

Quantum error correction

Implementation of quantum algorithms

Machine learning methods

Simulation of quantum systems

Quantum technologies exposure

Benchmarking tools for quantum computing

Quantum resource estimation

Quantum circuit optimization

Education

Master's program at an accredited college or university

Job description

At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget.

Our Science & Technology directorates include National Security, Earth and Biological Sciences, Physical and Computational Sciences, and Energy and Environment. In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus.

The Physical and Computational Sciences Directorate's (PCSD’s) strengths in experimental, computational, and theoretical chemistry and materials science, together with our advanced computing, applied mathematics and data science capabilities, are central to the discovery mission we embrace at PNNL. But our most important resource is our people—experts across the range of scientific disciplines who team together to take on the biggest scientific challenges of our time.

The Advanced Computing, Mathematics, and Data Division (ACMDD) focuses on basic and applied computing research encompassing artificial intelligence,applied mathematics, computing technologies, and data and computational engineering. Our scientists and engineers apply end-to-end co-design principles to advance future energy-efficient computing systems and design the next generation of algorithms to analyze, model, understand, and control the behavior of complex systems in science, energy, and national security.

The Future Computing Technology Group at the Pacific Northwest National Laboratory (PNNL) is seeking highly motivated Master’s interns for 2026.

Responsibilities

• Contribute and research a variety of topics with close collaboration with staff scientists
• Present research progress and work in weekly team meetings, communicating progress and results
• Engage with interns, post-docs and staff scientists in helping develop the quantum ecosystem capabilities

The internship is three months long, subject to extension based on performance and project needs. Interns can engage in cutting‑edge research and contribute to impactful projects alongside our world‑class team. This position will collaborate with a team in New York City.

Qualifications

Minimum Qualifications

• Candidates must be matriculated/enrolled in a Master's program at an accredited college or university.
• Minimum GPA of 3.0 is required.

Preferred Qualifications

• Understanding of quantum error correction, detection, and mitigation techniques.
• Interest or experience in implementing quantum algorithms and protocols on near‑term quantum hardware.
• Familiarity with machine learning methods as applied to quantum computing.
• Experience or coursework involving machine learning for simulating quantum systems.
• Exposure to emerging quantum technologies such as neutral atom systems or erasure qubits.
• Interest in developing benchmarking, verification, and validation tools for quantum computing.
• Understanding of quantum resource estimation for NISQ (Noisy Intermediate-Scale Quantum) and fault‑tolerant quantum computing (FTQC).
• Experience or coursework related to quantum algorithm development and optimization.
• Familiarity with quantum circuit optimization and transpilation for NISQ and FTQC systems.