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local heat solutions for PEDs. The EmPowerED project involves in total 11 PhD positions at several universities, focusing on different aspects of positive energy districts. The project also involves a
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Learning Centre; A complete educational program for PhD students; Multiple courses on topics such as time management, handling stress and an online learning platform with 100+ different courses; 7 weeks
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of parameters that improve process performance and material quality. Secondly, different machine learning strategies based on traditional supervised learning techniques (e.g. random forest (RF
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work will focus on identifying the mathematical knowledge and properties to guide hardware optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g
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. Your work will focus on identifying the mathematical knowledge and properties to guide hardware optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g
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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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of algorithms and digital neuromorphic hardware is an additional avenue for enhancing the efficiency of the methods. In this context the research will explore digital, event-based implementations
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temporal patterns across different neurons in the neocortical circuit and use them for closed-loop brain stimulation. By examining how these spatiotemporal dynamics relate to behaviour, you will develop new
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advance the development of the Tool’s algorithms and functionality. As a key innovative component of D-Suite, this open-source tool will achieve wide industry visibility, and will be formally evaluated by
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
Thermography. This raw dataset is needed to be processed and annotated to train supervised and unsupervised AI models. The research will aim to develop deep learning algorithms for damage classification