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sits at the intersection of AI Safety and Data-Centric AI. We aim to make large-scale ML more reliable, transparent, and aligned with human values. We are specifically interested in: Data-centric AI
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theoretical modelling. The project will focus on self-learning active mechanical networks, but will be tailored to align with the interests and expertise of the successful candidate - we will mutually ensure
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in finite-element analysis Experience in medical image analysis and data processing Basic knowledge of and/or experience in AI-driven models The ability to manage multiple tasks effectively Excellent
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Design effortless public transport solutions in a trans-disciplinary environment, collaborating with multiple stakeholders from academia, government and industry. Job description Using public
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, digitalisation, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future. At TU Delft, our people make
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smart mobility every day. Our education and research are directly aligned with what society needs now and in the future. At TU Delft, our people make the difference. With their knowledge and curiosity
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education and research are directly aligned with what society needs now and in the future. At TU Delft, our people make the difference. With their knowledge and curiosity, our staff provide a high-quality
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measures across multiple zebrafish models of leukodystrophy, including models of RNASET2 deficiency, adrenoleukodystrophy (ALD), Krabbe disease and metachromatic leukodystrophy (MLD). Zebrafish are widely
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salient features underlying its function in signaling can be highlighted: (1) it interacts with more than seventy binding partners, (2) it is heavily phosphorylated at multiple sites by at least eight
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and dynamic regulation for GPAI governance. Topic 2 - Encoding ethical principles in model alignment. Topic 3 – Improving risk awareness in the use of GPAI. Topic 4 – Countering the malicious use