Sort by
Refine Your Search
-
Category
-
Country
-
Employer
- CNRS
- AALTO UNIVERSITY
- Lawrence Berkeley National Laboratory
- Oak Ridge National Laboratory
- University of California
- University of California, Merced
- APCTP
- Aalto University
- Aix-Marseille Université
- Daegu-Gyeongbuk Institute of Science and Technology
- Delft University of Technology (TU Delft); yesterday published
- Episteme
- Fudan University
- Institut des Hautes Etudes Scientifiques
- Institut des Hautes Études Scientifiques
- Institute of Mathematics of the Czech Academy of Sciences
- National Yang Ming Chiao Tung University
- Pennsylvania State University
- Rutgers University
- Technical University of Denmark
- Technical University of Munich
- University of California Merced
- University of Minnesota
- University of New Hampshire – Main Campus
- University of Oklahoma
- University of Oxford
- University of Texas at Dallas
- Virginia Tech
- 18 more »
- « less
-
Field
-
the full stack, and develop scalable classical simulations (e.g., tensor networks)--including performance bounds beyond brute-force classical simulability. This role is deeply collaborative with the Advanced
-
the other is on a special grant on tensor networks and quantum computing for high-energy physics. Candidates interested in these and related topics are particularly welcome to apply. Successful candidates
-
related field, and a strong research background in mathematics. We particularly value experience in the following topics: vertex operator algebras, infinite dimensional Lie algebras, tensor categories
-
Monte Carlo, neural quantum states, tensor networks, machine learning and data science, dynamical mean field theory, diagrammatic Monte Carlo, etc.) Key Responsibilities Conduct independent and
-
, theoretically grounded, and explainable. The research sits at the crossroads of quantum information science, tensor network theory, and generative modeling (transformers, diffusion models, etc.). Key research
-
simulation tools for correlated attosecond electron dynamics in molecules." The position will involve developing new methods related to tensor network states (e.g. TD-DMRG, MCTDH) to simulate correlated
-
algebras, tensor categories, lattice models of statistical physics, conformally invariant random processes, formalization of mathematics (preferably in Lean). The working language of the group is English
-
background in mathematics. We particularly value experience in the following topics: vertex operator algebras, infinite dimensional Lie algebras, tensor categories, lattice models of statistical physics
-
/quantum-circuit techniques and/or approximate tensor-network methods. Analytical skills with integrability, random-matrix theory, dual-unitary circuits, hydrodynamics, or field-theoretic methods are also
-
techniques such as tensor networks, quantum Monte Carlo, ab initio calculations, and AI/ML is a plus. Minimum Education and Experience Ph.D in a related field. Preferred Education and Experience Other