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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 preferably should be enrolled in a Ph.D. program (but motivated master's or undergrads are also considered) 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 are now open for 2024 and 2025. Please inquire at [email protected] 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
Theory of circuit Quantum Electrodynamics Systems
Science and technology communication
Software Engineering for Data Analysis and High Performance Computing
Quantum Academy Participants
Numerical models for optimization hardware
Large-scale VQE simulations with Tensor Networks
Error Mitigation for Gate-Model Quantum Computing
Generative learning with the quantum approximate optimization algorithm
Mathematical investigation of QAOA
Benchmarking Flight Anomaly Detection Models with Discrete Latent Spaces
Efficient Implementation of Coherent Ising Machine using FPGA
Application of DeepONets with Physics-Informed Aspects for Combination Optimization
Implementation of the Mixer Phaser Ansatz
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A flexible high-performance simulator for verifying and benchmarking quantum circuits implemented on real hardware
NSF Expedition Science Communication and Software Development
Benchmarking of Quantum and Classical Stochastic Solution Methods
Benchmarking Stochastic Parameterized Methods with Collective Autonomous Mobility Problems
Algebraic Geometrical Methods for Compilation of Algorithms in Quantum Devices
Noise amplification at spin-glass bottlenecks of quantum annealing: a solvable model
Self-Consistent Quantum Truncation
Performance of a Quantum Annealer for Ising Ground State Computations on Chimera Graphs
Energy-based machine learning models for wildfire detection
Decomposition methods for discrete optimization problems leveraging Ising solvers
Quantum noise model and quantum error mitigation
Algorithm-specific benchmarking and error mitigation techniques
Code development for quantum algorithm on quantum hardware
Power of Pausing: Advancing Understanding of Thermalization in Experimental Quantum Annealers
NSF Expeditions project RIACS Software Development
Simulation of Non-Unitary Transformation
Extensions to QAOA
Quantum Alternating Operator Ansatz and Constrained Quantum Annealing
Resource and performance estimates for applications of quantum computing
Extending QAOA to solid state and molecular systems
Krylov subspace methods for Variational Quantum Eigensolvers
Studying noise in QAOA
Noise in quantum optimization circuits
Benchmarking the Coherent Ising Machine
Influence of noise on QAOA with XY mixers
Benchmarking Quantum Computers for Wireless Networks Applications
Hardware-Accelerated Parallel Tempering and Non-Equilibrium Monte Carlo Methods
RIACS Quantum Software & Training
Investigation of Unitary Techniques for Open Systems
MIMO Detection on an all-FPGA Ising Machine
Quantum Speedups for Distributed Graph Algorithms in the CONGEST-CLIQUE Model
Resonant approach to transverse field Grover’s search
Decomposition Methods for Discrete Optimization Problems Leveraging Ising Solver
Parameter Setting for D-Wave Quantum Annealers
Improving QAOA with Ancilla Qubits
Quantum annealing mappings and implementation of Steiner Tree problems
Neural Network Verification via Mixed-Integer Quadratic Optimization
Hardware efficient Quantum Algorithms
Simulation of Fermi-Hubbard Models
Benchmarking Tensor Network Classical Simulations of the Kitaev Model Against Quantum Circuit-Based Algorithms
Compiling a Quantum Approximate Optimization Algorithm Solver
Resource estimates and bounds for quantum state preparation
Online Quantum Workforce Development Courses and Training
Science Communication and Analysis of Quantum Machine Learning and Optimization Circuits
From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz
Integrative Research in Emerging Technologies
Population transfer in combinatorial optimization
Research in quantum time dynamics
Improvements on calibration of superconducting qubits
Quantum annealing approaches to graph connectivity problems
