Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- CNRS
- Lawrence Berkeley National Laboratory
- Oak Ridge National Laboratory
- University of California
- University of California, Merced
- APCTP
- Aix-Marseille Université
- Delft University of Technology (TU Delft); yesterday published
- Duke University
- Fudan University
- Institute of Mathematics of the Czech Academy of Sciences
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Michigan State University
- RIKEN
- Rutgers University
- Technical University of Denmark
- Technical University of Munich
- UNIVERSITY OF VIENNA
- University of Arizona
- University of California Merced
- University of New Hampshire – Main Campus
- University of Oklahoma
- Yale University
- 13 more »
- « less
-
Field
-
communication with a record of leading and reporting results. Desired Qualifications: Knowledge of quantum computing algorithms. Familiarity with tensor network methods. Experience programming GPUs. Experience
-
oral communication with a record of leading and reporting results. Desired Qualifications: Knowledge of quantum computing algorithms. Familiarity with tensor network methods. Experience programming GPUs
-
nonadiabatic nuclear dynamics simulations using tensor network states (ML-MCTDH) of vibronic coupling models. Of particular interest are candidates who have a background and/or interest in one or more of the
-
. Baschnagel. Correlations of tensor field components in isotropic systems with an appli- cation to stress correlations in elastic bodies. Phys. Rev. E, 108:015002, 2023. [7] J. P. Wittmer, A. N. Semenov, and J
-
metric tensor associated with the growth field: The further Ricci is away from zero, the more incompatibility. The goal of this project is to better understand the mechanical origin of residual stress in
-
University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 4 hours ago
capabilities to produce and polarize the solid targets needed for this program. In the near term, our group will focus on the Jefferson Lab Azz and b1 experiments, which will probe tensor po- larized deuterons
-
, Mixture-of-Experts; distributed training/inference (e.g. FSDP, DeepSpeed, Megatron-LM, tensor/sequence parallelism); scalable evaluation pipelines for reasoning and agents. Federated & Collaborative
-
processing, convex optimization, distributed processing, machine learning, and tensor analysis. Our applications span various domains, including audio and acoustics, wireless communication, radio astronomy
-
-spin theory, tensor gauge field theories, and field theory methods for strongly correlated systems. We encourage applications from candidates of all backgrounds, especially those from groups historically
-
-based electronic structure methods, quantum Monte Carlo, tensor networks, or quantum embedding methods, etc. -ML-augmented numerical method development. -High-performance computing (HPC). Certifications