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research software and working with high-performance or GPU computing environments. Experience publishing or contributing to scientific articles or conference papers. Personal qualifications Good
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architectures and embedded platforms (ARM Cortex-M, NPU, FPGA, embedded GPU), e.g., via academic courses and/or project courses Research experience (e.g., through a Master thesis work or research internships) is
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-related discipline. 2) Strong programming ability in optimisation or machine learning (e.g., Python/Matlab/C++; PyTorch/TensorFlow). Experience in signal processing/wireless or SDR/GPU prototyping is a plus
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computing and GPU infrastructure for the development and evaluation of LLM-, VLM-, and agentic AI solutions Research across the entire automotive software development lifecycle, from requirements and software
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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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written presentation skills in Norwegian, or another scandinavian language Experience with the CUDA programming model for general-purpose GPUs Experience with the OpenCL programming model Experience with
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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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, 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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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