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multi-center data challenges. Collaborating within Data Interpretation Task Forces (DITFs) to improve variant interpretation and assess the clinical relevance of both coding and non-coding variants
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network, PNAS 121, e2319718121 (2024) Qualifications We seek candidates with a strong background in physics, mechanical engineering, materials science, or computer science with an interest in complex meta
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Resonance Spectroscopy (MRS), and (resting state) network analyses), neurocognitive data (Amsterdam Cognition Scan), and explore new cross-modal methodological approaches to assess their relationship with
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to work on the design and implementation of Oscillatory Neural Networks (ONNs) for physics-based computing applications. You as the candidate will be an integral part of the prestigious NWO AiNED AI-on-ONN
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are currently seeking a highly motivated PhD student to join our team to work on the design and implementation of Oscillatory Neural Networks (ONNs) for physics-based computing applications. You as the successful
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international centre of knowledge: It belongs to the best research universities in Europe and is allied with prestigious partner universities and networks worldwide. The Faculty of Arts The Faculty of Arts is a
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Requirements A master’s degree in a relevant field (e.g computational design, advanced robotic fabrication, architecture). Experience working on topics related to 3d clay printing, custom g-code and slicer
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of infrastructure networks, which remain fragmented and hinder the coordination needed to address cross-sectoral implications of demand changes (e.g., modal shifts, the use of home batteries). At the same time
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/GPUs. These devices provide massive spatial parallelism and are well-suited for dataflow programming paradigms. However, optimizing and porting code efficiently to these architectures remains a key
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straining electricity grids, which are further challenged by the variability of renewables. Expanding grid capacity is both costly and slow. District heating and cooling networks (DHCNs) offer a smarter, more