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) are among the protection layers for our groundwater systems. They seal and compartmentalise aquifers, protecting drinking-water reservoirs from contamination, separating different groundwater compositions
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individual variability. Moving beyond classical localisationist accounts, the project aims to understand how language functions arise from large-scale network organisation and how these networks differ across
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challenging for classical computing architectures. Some of your responsibilities will include: Design and develop mixed-signal circuits for implementing ONNs. Modeling, simulate and benchmark different
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analog circuits for implementing ONNs for computing. Modeling, simulate and benchmark different computing tasks such as sensor data processing. Explore ONN implementation topology and its energy efficiency
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programming experience (e.g. Python, Matlab, C). Good organizational and communication skills. Ability to work independently as well as within a team. Good command of written and spoken English. TU Delft (Delft
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learning video-AI models; b) assess representational alignment of bio-inspired deep learning models to the human brain. The bio-inspired models will be enriched with different temporal integration mechanisms
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structural mechanics. Be comfortable in at least one high-level programming language such as Python or Matlab. Be enthusiastic about interaction with Dutch industry partners to help realize and implement
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these methods to quantify phase transformation, plasticity, damage, fracture, and particle volume/sizes for the parameters space that is relevant for wafer handling. Map out the different regimes of silicon
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processing; experience with array processing or inverse problems is beneficial. Proficiency in programming languages such as C, C++, Python, or Julia/Matlab is advantageous. Background in computational
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, bioinformatics, computer science, or a related field. Experienced programmer – You are confident in languages such as Python, Matlab or R, and you enjoy building and improving computational pipelines. Proficient