Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
volume, OpenFOAM, parallel computing, HPC. Knowledge and experience in suspension fluid mechanics, continuous modelling of granular media, non-Newtonian fluids, and smoothed particle hydrodynamics will be
-
Introduction to the university’s talent recruitment policy Main forum of the International Youth Scholars Forum Keynote report I Keynote report II 2:00 PM-17:30 Sub-forum of Capital Medical University Parallel
-
Learning codes using high performance computing (HPC)” Specifically, the candidate will carry out research tasks for the design, implementation, and evaluation on HPC systems of parallel algorithms in
-
simulation environment. Contribute to the implementation of search systems and optimization of the parallelization of AI models or system topology to minimize time and energy consumed. Where to apply Website
-
optimize large-scale distributed training frameworks (e.g., data parallelism, tensor parallelism, pipeline parallelism). Develop high-performance inference engines, improving latency, throughput, and memory
-
(AWS, Azure/GCP) Experience in open source software development. Knowledge of GPU-based computing, including multi-gpu/multi-node parallelization techniques will be valued. Fluency in spoken and written
-
conducted to investigate the relationships between disc morphology, biomechanics, and the expression of molecular markers such as MMP3, ADAMTS4, collagen types I and II, and aggrecans. In parallel, a second
-
including knowledge of PyTorch, Tensorflow, Pandas, Scikit-learn and/or Numpy. Knowledge of GPU-based computing, including multi-gpu/multi-node parallelization techniques. Fluency in spoken and written
-
parallel, we focus on engineering metamaterial structures at subwavelength scales to achieve unprecedented electromagnetic, acoustic, or mechanical properties not found in natural materials. We
-
-Based Generative Models: How can we fundamentally redesign generation processes for superior efficiency, controllability, and quality? We are exploring diffusion models, flow-matching, and other parallel