Sort by
Refine Your Search
-
Category
-
Employer
-
Field
-
intelligence models (LLMs) in multi-GPU environments. Preparation of technical documentation, best practices for development and operation. Where to apply Website https://sede.uvigo.gal/public/catalog-detail
-
. Knowledge and Professional Experience: DFT-based methods. Scientific programming in Fortran, in MPI/OpenMP-parallelised codes. Knowledge of other languages (in particular python) and of GPU offloading will be
-
(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
-
site-specific and realistic radio propagation data through GPU-accelerated ray tracing to train AI/ML algorithms. Exploring the use of generative models for wireless channel modeling, e.g., to produce
-
. Knowledge and Professional Experience: DFT-based methods. Scientific programming in Fortran, in MPI/OpenMP-parallelised codes. Knowledge of other languages (in particular python) and of GPU offloading will be
-
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
-
and aerial data. Analysis of large wildlife databases: neural networks. Computing clusters with CPU/GPU. Specific Requirements Educational Requirememts: Machine learning. Signal processing. Signal
-
working with climate, weather and earth datasets formats (netcdf, zarr,..) . Working knowledge of High-performance computing (HPC). Experience with GPU-accelerated machine learning frameworks such as RAPIDS