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- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); 16 Oct ’25 published
- Delft University of Technology (TU Delft); Published yesterday
- University of Amsterdam (UvA)
- University of Amsterdam (UvA); Published today
- Vrije Universiteit Amsterdam
- Vrije Universiteit Amsterdam (VU)
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Field
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strategies for programming, modeling, and integrating reconfigurable/spatial architectures, such as FPGAs and ML accelerators, within heterogeneous ICT ecosystems.Reconfigurable and Spatial hardware, such as
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). Strong academic background and competencies in parallel programming, distributed computing, and performance engineering. Familiarity with accelerator programming (e.g, GPU), hardware programming, high
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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; Eager to collaborate and
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Passionate about AI-driven perception for intelligent vehicles
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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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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
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recommended. Other valuable skills include: Experience in high-performance computing using MPI. Experience in GPU programming using OpenACC, CUDA, CUDA-Fortran, Julia, or related tools. Experience in CFD
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6G testbeds (indoor and outdoor) with GPU clusters and edge computing platforms Global Internet measurement infrastructure and satellite network access Opportunities to engage with Internet