Doctoral Researcher in quantum-inspired tensor network machine learning solvers for super-moiré van der Waals materials
Tasks
- Apply active learning tensor network tight binding strategies
- Compute collective quasiparticle excitations with tensor networks
- Compute transport in super moire systems
- Develop quantum inspired active Hamiltonian learning from spectroscopy
- Develop tensor network solvers for large quantum states
- Develop tensor network topological probes
- Simulate equilibrium and out of equilibrium quantum systems
Perks/Benefits
Skills/Tech-stack
Active Learning | Hamiltonian Learning | High Performance | High-Performance Computing | Julia | Machine Learning | Performance Computing | Python | Quantum Many-Body Methods | Quantum Physics | Quantum transport | Tensor Network Formalism | Tensor Networks | Tensor network | Tight Binding | Topological Probes
Education
Roles
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