Quantum Machine Learning - Postdoctoral Researcher

Company Description

Join us and make YOUR mark on the World!

Are you interested in joining some of the brightest talent in the world to strengthen the United States’ security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.

We are committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people, talents, ideas, experiences, and perspectives. This is important for continued success of the Laboratory’s mission.

Pay Range

$118,884 Annually

Job Description

We have an opening for a Postdoctoral Researcher to perform theoretical and computational research on the use of machine learning and quantum computing methods to accelerate Fusion Energy Sciences (FES) applications. You will join an interdisciplinary team of experts in fluid dynamics, plasma physics, machine learning, and quantum information science that are working to develop, implement, and demonstrate the performance of quantum-accelerated machine learning algorithms relevant to FES. You will explore the application of machine learning methods for dynamical systems to the physics of fluids and plasmas, develop quantum algorithms that accelerate the classical methods, and perform numerical simulations that characterize the performance of these algorithms. This position is in the Fusion Energy Sciences Program’s Theory and Modeling group within the Physics Division.

Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week.

You will

• Develop machine learning algorithms for fluid and plasma physics applications based on methods from Koopman operator theory.
• Explore the performance of these algorithms for tasks such as Koopman mode identification, model reduction, closure of fluid moment hierarchies, and subgrid-scale modeling.
• Develop quantum-accelerated machine learning algorithms based on Koopman operator theoretic methods for fluids and plasmas.
• Analyze, interpret and compare the results of simulations with respect to theoretical expectations.
• Contribute to and actively participate in the conception, design, and execution of research to address defined problems.
• Collaborate with others in a multidisciplinary team environment to accomplish research goals.
• Pursue independent and complementary research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory.
• Organize, analyze, and publish research results in peer-reviewed scientific journals and present results at conferences, workshops, seminars, and technical meetings.
• Perform other duties as assigned.

Qualifications

• PhD in Physics or related discipline.
• Experience developing and applying theoretical and computational models to the simulation of plasmas, fluids, or other physical systems and analyzing and interpreting the results of the models.
• Experience developing quantum algorithms and/or machine learning algorithms, working with quantum computing hardware platforms, and/or theoretical modeling of quantum physical systems.
• Ability to perform independent research and find innovative solutions to scientific and technical problems as demonstrated through publication of peer-reviewed literature.
• Proficient verbal and written communication skills needed to effectively present and explain technical information.
• Initiative and interpersonal skills necessary to collaborate effectively in a multi-disciplinary team environment.

Qualifications We Desire

• Knowledge of advanced theoretical and numerical methods for the simulation of plasma physics, fluid dynamics, and/or dynamical systems theory.
• Knowledge of ergodic theory, Koopman operator theory, and/or machine learning paradigms.
• Expertise in quantum algorithms, quantum information theory, quantum computing hardware platforms, and the analysis of the results of quantum computations.
• Programming proficiency in Python, Matlab, C++, Fortran, and/or other programming and scripting languages.
• Knowledge of quantum compiler/transpiler languages such as circ, qiskit, and/or qutip.

Additional Information

#LI-Hybrid

Position Information

This is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.

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