Machine Learning for Rydberg-Based Quantum Simulators internship - W/M
Tasks
- Benchmark against exact diagonalization
- Benchmark against raw QPU data
- Benchmark against tensor networks
- Benchmark against variational Monte Carlo
- Contribute to internal tools and publications
- Develop and train neural quantum states
- Pretrain neural quantum states on QPU generated datasets
- Represent observables and many body wave functions for magnetic Hamiltonians
Perks/Benefits
Skills/Tech-stack
Exact Diagonalization | High Performance | High-Performance Computing | JAX | Julia | Kernel methods | Machine Learning | Many-body physics | Monte Carlo | Neural Network | Neural Quantum States | Performance Computing | PyTorch | Python | Quantum Many Body | Quantum many-body physics | Supervised Learning | Tensor Networks | TensorFlow | Unsupervised Learning | Variational Monte Carlo
Education
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