Quantum Computing

Feynman Quantum Academy - Internship Program

An internship at the USRA-NASA Quantum Artificial Intelligence Laboratory (QuAIL) at NASA Ames Research Center's Advanced Supercomputing Facility introduces graduate students to scientific opportunities in quantum information sciences and trains them to do research related to the most advanced quantum computing platforms. Students will receive valuable experience working on teams, undertaking projects in advanced computing, and developing quantum and classical methods to solve problems in important application or fundamental domains. The program is funded by NASA, AFRL, USRA and NSF.

Students, which need to be enrolled in a Ph.D. program or have otherwise previous quantum computing research experience, are accepted to a 12-to-24 week program. Applications are open all year round. These students work in close collaboration with quantum scientists, receiving hands-on training, and undertake individualized research projects, finally resulting in a publication. Students will also participate in seminars and workshops with researchers from other organizations doing quantum research, including those from academic institutions, government laboratories, and commercial organizations. Participants receive a stipend to cover living expenses and travel during the program.

Applications for Winter and Spring 2020 are now open. Please inquire at dventurelli@usra.edu or click on "Apply Now!" at the top of the page and fill in the form.

Potential topics (not exhaustive list):

Quantum Optimization and Sampling Algorithms (e.g. QAOA/VQE/AQC)
Benchmarking NISQ Computers
Compilation/Embedding of Quantum Algorithms
Quantum error-mitigation and correction methods
Quantum Algorithms for Materials, Chemistry, Non-equilibrium systems and High-Energy Physics
Numerical Simulation of Quantum Systems
Noise Modeling and Open Quantum Systems
Physics of Oscillator Based Computing and Coherent Optical Ising Machines
Quantum Complexity Theory
(Quantum) Machine Learning applied to Quantum Computing

Quantum Academy Participants

2020
2019
2018
2017
2016
All
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Numerical models for optimization hardware

Abhishek Kumar Singh
Princeton University
Years participated: 2020
Sponsors
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Algorithm-specific benchmarking and error mitigation techniques

Jahan Claes
University of Illinois Urbana-Champaign
Years participated: 2020
Sponsors
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Code development for quantum algorithm on quantum hardware

James Sud
University of California Berkeley
Years participated: 2020
Sponsors
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Extending QAOA to solid state and molecular systems

Mao Lin
University of Illinois Urbana-Champaign
Years participated: 2020
Sponsors
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Studying noise in QAOA

Marti Vives
Princeton University
Years participated: 2020
Sponsors
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Noise in quantum optimization circuits

Matias Jonsson
Carnegie Mellon University
Years participated: 2020
Sponsors
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Benchmarking the Coherent Ising Machine

Matthew Kowalsky
Years participated: 2020
Sponsors
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Benchmarking Quantum Computers for Wireless Networks Applications

Minsung Kim
Princeton University
Years participated: 2019-2020
Sponsors
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Hardware efficient Quantum Algorithms

Ryan La Rose
Michigan State University
Years participated: 2019-2020
Sponsors
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Research in quantum time dynamics

Vladimir Kremenetski
University of California Berkeley
Years participated: 2019-2020
Sponsors