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to integrate the human findings and preclinical experimental data. Publish your results, present at international conferences, and contribute to departmental teaching activities. Are you eager to uncover how
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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 the difference. With their knowledge
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rapidly. That is why we focus on themes such as energy, climate, digitalisation, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society
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we focus on themes such as energy, climate, digitalisation, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and
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scientific challenges, including how to properly incorporate power systems physics into the foundation AI model architecture, as well as how to develop an architecture that is invariant to the distribution
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other disciplines, as required (mathematics, operations research). Within the team, we strive to develop methods that are mathematically rigorous and have near-term application potential. We are strong
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combines clinical expertise, data science and wearable sensor technology to develop new methods for measuring disease progression in Parkinson’s disease. You will investigate how digital biomarkers can
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compared to "classical" on-body sensors - design techniques for intra-oral medical sensors are much more stringent than for on-body sensors. For reference please read the following article https://dl.acm.org
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their relevance for weather, air quality and climate. We do research on a variety of topics and horizontal scales. As a university group we are responsible for the education in subjects of Meteorology and
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the Leiden Institute of Advanced Computer Science (LIACS). As a team, we develop cutting-edge techniques for advanced computational imaging systems, combining expertise from Mathematics (Inverse Problems