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Field
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, you will explore how data-driven models capturing the state-of-health and degradation can be integrated in the battery model. You will develop these machine learning-based proxies together with a
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Computer Science, Artificial Intelligence, Engineering or a closely related field; Solid background in machine learning and/or evolutionary optimisation; strong programming skills (Python/C++); Proven interest in
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Are you eager to support exciting research with ultracold atoms and trapped ions? Do you want to participate in the creation of complex machines that have never existed before? Do you enjoy sharing
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lead to better and fairer outcomes—challenges such as cognitive overload, uncalibrated (dis)trust in AI, and unclear strategies for bias mitigation limit its effectiveness in practice. This PhD project
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Centrum Wiskunde & Informatica (CWI) has a vacancy in the Machine Learning research group for a talented PHD-studenT iN NeuroAI of Developmental vision (m/f/x) Job description A PHD-studenT iN
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, electrical engineering, technical medicine, or a related field. You have a solid background in biomedical signal analysis, physiology dynamic system, and machine learning technologies, and preferably have
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Computational Fluid Dynamics (CFD) models; data-based models determined from training/calibration data by system/parameter identification and machine learning. The key challenge is striking a balance between, on
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challenges. As a part of your PhD research you will regularly visit our industrial and scientific partners to learn about the challenges and constraints. You will also study the problem in detail with
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collaborative labs develop and deploy the latest technology, including sensing, data analytics, modelling, simulation, artificial intelligence, and machine learning, and function as dynamic hubs where innovative
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theory, and machine learning. They will have access to a fully equipped lab and benefit from collaborations within the ERC team and across TU Delft. There will be opportunities to present at leading