PhD Intern - Quantum Computing
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.
Responsibilities
The Future Computing Technologies group at Pacific Northwest National Laboratory (PNNL) is seeking a PhD intern for Fall/Winter 2025 with a strong background in quantum error correction (QEC), AI for quantum computing, distributed quantum computing (DQC), and hybrid continuous-variable/discrete-variable (CV-DV) systems.
The selected intern will contribute to cutting-edge research as part of PNNL’s Department of Energy-funded quantum projects. This work involves close collaboration with researchers at PNNL, other national laboratories, universities, and industry partners. Areas of focus include the development, application, benchmarking, compilation, and optimization of quantum algorithms and software.
This internship can be completed on-site in Richland, WA (full-time, 40 hours/week), or remotely (part-time only, up to 20 hours/week).
Responsibilities and accountabilities include:
- Developing new algorithms for mapping linear algebra solvers (e.g., linear combination of unitaries, quantum signal processing, quantum Hamiltonian descent) to hybrid CV-DV systems
- Mapping domain and QEC applications to the tensor-network and stabilizer simulators of NWQSim
- Conducting research on compiler optimization for QEC codes such as quantum low-density parity-check (qLDPC)
- Publishing research findings in peer-reviewed venues such as top-tier computer science conferences or physics journals
- Collaborating with internal and external research staff and domain scientists
- Participating in, and potentially leading, technical presentations
- Engaging in regular team meetings and research discussions
Qualifications
Minimum Qualifications:
- Candidates must be currently enrolled/matriculated in a PhD program at an accredited college
- Minimum GPA of 3.0 is required
Preferred Qualifications:
- Educational background in computer science, quantum physics, or a related field
- Hands-on experience with Quantum Error Correction (QEC) codes
- Familiarity with quantum linear solver algorithms
- Knowledge of continuous-variable and discrete-variable (CV-DV) quantum systems
- Proficiency with Qiskit or other quantum computing frameworks
- Experience working with real quantum hardware such as IBMQ, Quantinuum, IonQ, IQM, or Rigetti
- Experience developing or deploying code on High-Performance Computing (HPC) clusters
- Familiarity with quantum transpilation and other circuit optimization techniques
- Experience with large language models (LLMs) and reinforcement learning (RL)