Sort by
Refine Your Search
-
Category
-
Country
-
Program
-
Field
-
take a leading role in the design, deployment, maintenance, and optimisation of large-scale HPC systems, including CPU and GPU clusters, high-performance storage, and advanced networking technologies
-
functioning in a dynamic technological environment. Preferred Qualifications: Experience with parallel computing, GPU operation (CUDA Toolkit), multi-GPU training, and distributed frameworks for machine
-
, or approximate computing. Knowledge of hardware security, fault tolerance, dependable computing, or hardware reliability. Experience with GPU, FPGA, embedded, or specialized AI accelerator platforms. Experience
-
and developing sustainable engineering solutions. Evaluate and introduce emerging technologies, architectures, and engineering approaches, including HPC, AI/ML, GPU computing, containers, and other
-
, GPU) and workshops for mechanical, electrical and electronic development projects. Long-standing and very successful cooperations with industry and clinical partners (cardiology, radiology) offer
-
research-focused HPC environment. Project background We train open foundation models with hundreds of billions of parameters on thousands of GPUs on one of the largest AI-ready supercomputers in Europe
-
Data (CRCD), which operates a large multi-thousand-core cluster with GPU co-processors and PhD-level consulting staff. Pitt ECE also leads the NSF Center for Space, High-performance, and Resilient
-
Data (CRCD), which operates a large multi-thousand-core cluster with GPU co-processors and PhD-level consulting staff. Pitt ECE also leads the NSF Center for Space, High-performance, and Resilient
-
/SCI Clearance Master’s degree Training and optimizing ML algorithms on GPU hardware architectures, specifically NVIDIA based Working with geo-spatial data Statistics, multivariable calculus, and linear
-
of CPU and GPU resources to maximize model performance, scalability, and portability. A particular focus of the position will be a dedicated project to prepare, optimize, and benchmark the code