Postdoc: AI for Quantum Computing & QEC

Oak Ridge National Laboratory; Oak Ridge (TN); On-site; USD 70,000 - 110,000; Full time

Job summary

Oak Ridge National Laboratory seeks a Postdoctoral Research Associate in AI for quantum computing to lead research combining deep learning with quantum error correction and real‑time QEC decoding. You will design AI‑driven workflows across Qiskit, PennyLane, CUDA‑Q, and Stim, benchmark algorithms on diverse hardware, and publish open‑source software.

The role offers access to leading quantum hardware and HPC resources, collaboration with QSC scientists, and opportunities to contribute to

Qualifications

• Conduct original research in AI for quantum computing, developing advanced machine learning models, neural decoders for quantum error correction, AI-driven error mitigation, and noise characterization algorithms.
• Design, build, and evaluate AI-assisted quantum workflows, combining deep learning architectures and multi-agent AI systems to automate circuit generation, QEC decoding, and experiment analysis across quantum software frameworks and hardware backends.
• Develop benchmarks and validation methods that test whether AI-generated quantum code, circuits, and analyses are physically and computationally correct.
• Implement and benchmark quantum algorithms and error-handling protocols on quantum hardware from multiple providers and modalities, and on GPU/HPC resources, to ground AI systems in realistic device behavior.
• Publish in leading peer-reviewed venues, release open-source software, contribute to proposals, mentor students, and collaborate across ORNL and with academic, industry, and national laboratory partners.

Responsibilities

• Conduct original research in AI for quantum computing, developing advanced machine learning models, neural decoders for quantum error correction, AI-driven error mitigation, and noise characterization algorithms.
• Design, build, and evaluate AI-assisted quantum workflows, combining deep learning architectures and multi-agent AI systems to automate circuit generation, QEC decoding, and experiment analysis across quantum software frameworks (such as Qiskit, PennyLane, CUDA‑Q, Stim) and quantum hardware backends.
• Develop benchmarks and validation methods that test whether AI‑generated quantum code, circuits, and analyses are physically and computationally correct.
• Implement and benchmark quantum algorithms and error‑handling protocols on quantum hardware from multiple providers and modalities, and on GPU/HPC resources, to ground AI systems in realistic device behavior.
• Publish in leading peer‑reviewed venues, release open‑source software, contribute to proposals, mentor students, and collaborate across ORNL and with academic, industry, and national laboratory partners, following ORNL policies for sensitive information and cybersecurity.

Skills

AI for quantum computing

Deep neural architectures

Quantum error correction

Multi-agent AI systems

Noise learning

Education

PhD in a related field

Tools

Qiskit

PennyLane

CUDA-Q

Stim

Job description

Oak Ridge National Laboratory seeks a Postdoctoral Research Associate in AI for quantum computing to lead research combining deep learning with quantum error correction and real‑time QEC decoding. You will design AI‑driven workflows across Qiskit, PennyLane, CUDA‑Q, and Stim, benchmark algorithms on diverse hardware, and publish open‑source software.

The role offers access to leading quantum hardware and HPC resources, collaboration with QSC scientists, and opportunities to contribute to