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Field
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conduct world-class applied research. We change and make a difference. Do you want to become one of us? The Department of Computer Science (DIDA) is one of three departments at the Faculty of Computing
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Engineers. Serve as liaison with Princeton Research Computing staff on GPU cluster related issues. Professional Development Learn the underlying science, mathematics, statistics, data analysis, and algorithms
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Memorial Sloan-Kettering Cancer Center | New York City, New York | United States | about 2 months ago
capabilities. We can access a high-performance computer cluster with the most advanced GPU resources. We also partner with the New York Proton Center, which houses one cyclotron, three rotational gantry
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, PyTorch/TensorFlow) experience working with cluster/GPU computing resources is desirable excellent verbal and written communication skills and the ability to work effectively in a collaborative team
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with edge computing or embedded systems (e.g., NVIDIA Jetson, Raspberry Pi) Background in real-time processing and GPU acceleration (CUDA) Participation in relevant competitions (e.g., Kaggle, computer
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Your Job: Investigate the potential of novel computing architectures for lattice field theory workloads Contribute to the design and implementation of an open-source lattice field theory framework
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GPU utilization and allocate computing resources efficiently across users. c) create and manage user accounts for faculty and students; troubleshoot user issues; and design and deliver
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robust biologically optimized Radiation Therapy to mitigate patient radiosensitivity uncertainty. 1) transfer of matRad code to a GPU computer for rapid simulation of biologically optimized treatment plans
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Emirates Application Deadline 4 Feb 2026 - 00:00 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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significant computational component in deploying multi-GPU codes to efficiently train on the large, densely-connected and graph-structured data encountered in our systems of interest. Your contributions would