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well as large-scale GPU computing facilities for deep learning. We are looking for a Research Engineer to manage the EEE GPU Cluster. The role will focus on enhancing the EEE GPU Cluster team’s ability in terms
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Internal Number: 25597 INFORMATION SECURITY MANAGER, The Massachusetts Green High Performance Computing Center (MGHPCC ), to serve as the primary security leader across MGHPCC and the AI Computing Resource
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studies. These pipelines must be capable of efficiently exploiting different types of parallelism, both at the level of a computing node (CPU and GPU) and at the level of a cluster of PCs. This environment
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at https://postdoc.hms.harvard.edu/guidelines . With this appointment, you are represented by the Harvard Academic Workers (HAW) – UAW for purposes of collective bargaining and matters affecting your
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programming (Python, C++, etc.) and machine learning and signal processing libraries; You have HPC/GPU computing experience, including running deep learning workloads on compute clusters (CUDA-compatible GPUs
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modeling). Experience working with HPC/GPU resources and job schedulers (e.g., Slurm) and/or cloud-based deployments. Track record of contributing to peer-reviewed publications as a computational specialist
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FLAME-GPU accelerated agent-based modelling of material response to environmental and operational loading EPSRC CDT in Developing National Capability for Materials 4.0, with the Henry Royce
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Master degree in Informatics Website for additional job details https://www.unimc.it/it/ateneo/bandi-e-concorsi/finaziamenti-ricerca/borseattiv… Work Location(s) Number of offers available1Company
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INGEGNERIA INDUSTRIALE | Italy | 21 days ago
Description Analysis and development of methodologies to accelerate the computation of numerical optimization through parallelization and the use of GPUs. Where to apply Website http://www.unibo.it Requirements
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Job Code 0005 Employee Class Civil Service Add to My Favorite Jobs Email this Job About the Job The successful applicant will assist in the adaptation of the PPMstar code to run well on GPU-accelerated