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with leading machine learning frameworks and modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds GPUs, are required. Additional Qualifications
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, IEEE IV and RadarConf. For your research, you will have access to extensive computing resources at TU Delft, ranging from personal workstations and shared GPU servers to the Delft AI Cluster and the
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/ coarse- grained approaches) Experience with enhanced sampling techniques; computational biophysics/chemistry Usage of high-performance computing clusters, preferably GPU-based computing Proficiency in
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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
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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
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shared GPU servers to the Delft AI Cluster and the DelftBlue supercomputer. Your supervisors will be Prof. Dariu Gavrila and Dr. Julian Kooij. Job requirements We are looking for a candidate with: An MSc
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/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
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. The Directorate comprises the International Office, led by the Deputy Director International; the Global Partnerships Unit (GPU), led by the Associate Director Transnational Education (TNE); DMU Global; and the
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for GPU-based AI workloads, with control at the level of transformer blocks and attention layers. • Design and build a high-resolution (microsecond-scale) performance monitoring framework to capture
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, or population genetics Deep learning for sequence, EHR, or imaging data High-performance and GPU computing environments Excellent candidates from adjacent quantitative fields are encouraged to apply. The Research