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clinical data, high-end GPU resources, and integration into TWIN-X, an EU Horizon Europe consortium with 18 partners from 12 European countries. You will work with data from TUM University Hospital and
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selection criteria Good oral and written presentation skills in Norwegian, or another scandinavian language Experience with the CUDA programming model for general-purpose GPUs Experience with the OpenCL
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datasets, high-end GPU and storage infrastructure, international research collaborations, and dedicated funding for international conference participation. Supervision The PhD candidate will be supervised by
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, e.g., git, automated testing, packaging, documentation and code review. Experience with GPU computing or high-performance computing. Interest or experience in LLMs, tool-using agents, or agentic
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, and validated through simulation and experiments. For experiments, IDLab-UAntwerp's world-class research infrastructure, including GPU Lab, Software Defined Radios and programmable beamformers, as
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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
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of machine learning and clinical oncology, with access to a large multimodal research dataset, substantial GPU resources, and a collaborative scientific environment. Your tasks Design and implement LLM-based
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trading strategies. We work with petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing thousands of high-end GPUs. Depending on the day, we might
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responsible for: Conducting research on sustainable and resource-efficient AI systems for edge datacentres. Creating hardware-aware search spaces for CPUs, GPUs, and accelerators, and developing multi-objective
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available to a University in the world. It includes 49,920 AMD cores for traditional computing and 608 NVIDIA GPUs for artificial intelligence analyses. The University of Florida Genetics Institute is an