Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
, MATLAB, Git, debugging, and modern software engineering practices. Experience with GPU computing (e.g., CUDA, HIP), parallel computing (e.g., MPI, Actor Model). Familiarity with containerization (e.g
-
development and enhancement of our multi-scale multi-physics suite of software, and their deployment on the university HPC & GPU based system. The position is primarily research and enterprise, but there would
-
-efficient designs, GPUs and HPC), Data Science/AI/Machine Learning (e.g., fundamentals, trust and explainability, LLMs, autonomous systems, computer vision), Security (e.g., fundamentals, hardware/software
-
-on experience in one or more of the following technology areas: hardware/software co-design, performance optimization with heterogeneous and alternative computing systems (CPU/GPU/NPU/etc.), FPGA design, high
-
released SecureData4Health (SD4H) OpenStack cloud infrastructure. It currently includes 15,000 VCPU, 60 Petabyte of storage, 30 GPU and is growing as additional academic research projects join. The Software
-
research and opportunities for collaboration inside and outside of the University. The Centre has access to extensive dedicated computing resources (GPU, large storage). The successful applicant will work
-
, parallel/distributed computing, as well as diverse architectures and understanding of its impact on application performance Knowledge in GPU-based programming and modelling of scientific simulations
-
dynamic research environments, exhaustive training opportunities and institutional collaborations. The PhD candidate will benefit from the computational resources available at CEPAM (GPU servers). He/She
-
enterprise-wide resource designed to support and advance Hopkins research mission through flexible computing, storage, and networking infrastructure. The facility provides high-end computational CPUs, GPUs
-
. Prior work with databases used for organizing large-scale processing. Prior use of and/or software development with GPUs. Experience with visualization of large data sets. An understanding of how to make