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- Delft University of Technology (TU Delft)
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- Delft University of Technology (TU Delft); 16 Oct ’25 published
- Delft University of Technology (TU Delft); Published yesterday
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- Leiden University; today published
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- Max Planck Institute for Psycholinguistics; today published
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Field
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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code
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Specific Integrated Circuits (ASIC), Processors (CPU, GPU, VPU and accelerators), Field Programmable Gate Arrays (FPGA) and System-on-Chips (SoCs), as well as Intellectual Property (IP) Core developments for
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platforms such as llm servers, shared virtual GPUs (VGPUs) used by OPS-G, and the broader utilization of cloud resources. Ensuring the smooth operation, availability, and continuous improvement
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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code
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segmentation." CVPR. 2022. [3] van Spengler, Max, and Pascal Mettes. "Low-distortion and GPU-compatible Tree Embeddings in Hyperbolic Space." ICML. 2025. [4] Pal, Avik, Max van Spengler, Guido Maria D'Amely di
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resources of TU Delft, ranging from personal machines, to shared GPU servers, the Delft AI Cluster that is shared across departments, as well as DelftBlue , which is one of the top 250 supercomputers in
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background in machine learning, deep learning, and/or computer vision; Experience in programming. Python is a must, lower-level GPU programming experience is a bonus; Strong grasp on the English language
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small cluster computers, high-end GPU nodes and specially configured workstations on which experiments are conducted. You will be working in a team of junior and senior system administrators. Naturally
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equipment such as small cluster computers, high-end GPU nodes and specially configured workstations on which experiments are conducted. You will be working in a team of junior and senior system administrators
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in high-performance computing using MPI. Experience in GPU programming using OpenACC, CUDA, CUDA-Fortran, Julia, or related tools. Experience in CFD meshing software. TU Delft (Delft University