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to source localization based on microphone arrays or distributed sensors. This PhD project will focus on the development of novel methods and algorithms for airborne noise source localization in generic urban
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to the research; Good understanding of computer architecture; Basic understanding of MRI algorithms is a plus; Understanding of AI and its practical implementations; The ability to work in a team and take
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To boldy go where no man has gone before. Job description The PostDoc position is part of research of prof. Bernd Rieger and prof. Sjoerd Stallinga, in which we target (super-resolution) microscopy
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availability, more attractive working hours at service locations, and decreased train unit movements for regular maintenance. New innovative approaches need to be developed to schedule rolling stock
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this PhD project, you will investigate the co-design between event-based learning algorithms and neuronal hardware units with multi-scale time constants. The algorithmic methodology will exploit recent
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the security and cyber domain, with special focus on ethics and algorithmic transparency; Human-Technology Interaction: Developing robots, simulations, and games, which use a variety of AI technologies to learn
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electrical power, enabling smart sensors to operate without batteries. You will explore novel capacitor-based rectifier architectures, adaptive impedance-matching algorithms, and on-chip protection mechanisms
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Join TU Delft and work together with NXP to build low-power AI accelerators for self-healing analog/RF calibration, fixing noise/offset. Co-design algorithms & hardware and validate on real silicon
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based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored, and the findings of your project will be
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, prove the convergence and stability of swarm behaviour, and validate novel control strategies that quickly adapt to rapid changes in supply/demand. New effective market, contracting, and algorithmic