-
megawatts. To transfer energy efficiently from the grid to CPUs/GPUs, higher system voltages are required in data centres/computer racks, and efficient power electronics converter systems based on SSTs
-
applications. HPC and orchestration of scientific data processing workflows. Parallel computing (GPU & CPU). good software engineering practices for scientific software (version control, testing, continuous
-
, including running large-scale machine learning models (e.g., PyTorch, JAX) on GPUs in an HPC environment and maintaining reproducible workflows. Extensive prior experience developing pipelines and analytic
-
metrics and usage statistics, identify inefficiencies on different levels (CPU/GPU, I/O patterns, etc.) and provide corresponding reports. You will work closely with researchers and HPC users and provide
-
(CPU/GPU), numerical modeling/Monte Carlo simulations are an asset Visualisation skills are an asset Careful way of working, checking of results Candidates can have an M.Sc. degree in STEM, or a Ph.D
-
the Alps supercomputer at the Swiss National Supercomputing Centre (CSCS), which features over 10,000 NVIDIA Grace Hopper GPUs, making it one of the most powerful AI-focused computing resources in