Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
in high-performance computing using MPI. Experience in GPU programming using OpenACC, CUDA, CUDA-Fortran, Julia, or related tools. Experience in CFD meshing software. TU Delft (Delft University
-
projects at CASS. The center fellows will have access to a 70,000-core Infiniband Cluster (Jubail) dedicated to the science division, several GPU-based clusters at NYUAD, and other supercomputer facilities
-
, managed directly by CARC staff, include multiple compute clusters that include state-of-the-art GPU resources, dedicated enterprise and high-performance storage systems, high-speed networking systems, and a
-
, or emerging technologies); Python fluency plus a second server-side language; cloud & GPU proficiency; record of mentoring. Preferred – Master’s degree; expertise in TypeScript and good architectural
-
configuration and management tools (e.g. SLURM, Ansible). Knowledge of or experience in networking systems, including DNS, HTTP, and TCP/IP. Experience with secure data processing and storage. Experience with
-
environment, which brings together more than 400 researchers across disciplines. The collaboration provides access to substantial computational resources (GPU nodes), advanced high-throughput instruments
-
(Jubail) dedicated to the science division, several GPU-based clusters at NYUAD, and other supercomputer facilities through the CASS network. NYUAD also has guaranteed observing time on the Green Bank
-
signal processing and/or survey datasets. ML & AI techniques and applications. HPC and orchestration of scientific data processing workflows. Parallel computing (GPU & CPU). good software engineering
-
, combining scientific excellence with real-world impact. They operate within a unique ecosystem that includes the AI Foundry (state-of-the-art GPUs and engineering capacity), the System for User Knowledge (SUK
-
3T Siemens MR scanners, OPM-MEG, EEG, eye tracking, and TMS laboratories. They will also have access to Princeton's world-class computational infrastructure, including GPU systems capable of running