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works have shown that for embedding hierarchies, we should abandon Euclidean geometry altogether and operate in hyperbolic space [1]. Our lab has published multiple papers showing that hyperbolic deep
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for individuals living with multiple long-term conditions known as multimorbidity, and may lead to unnecessary polypharmacy. This PhD studentship aims to develop a Bayesian modelling framework to identify clusters
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processing, embedded systems, machine learning, and networked communication. Each PhD position corresponds to a dedicated research topic within the consortium. All doctoral researchers will benefit from joint
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About the Project The future power grid will be a highly complex cyber-physical system, integrating multiple distributed energy resources (DERs) such as solar, wind, marine, and bioenergy alongside
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designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
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issue is the embedding of hierarchies, for which a different geometry is better suited, namely hyperbolic geometry. Seminal works have shown that for embedding hierarchies, we should abandon Euclidean
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be recruited of which this PhD project is one and will be embedded in the whole consortium project. Below the description of the PhD project “New Partnerships between citizen collectives and
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embedded in the whole consortium project. Below the description of the PhD project “New Partnerships between citizen collectives and governments” will be given. Challenges: Collaborative relationships
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. For complex conditions such as multiple sclerosis and autism spectrum disorder, progress has been slowed by animal models that optimize for single causes or treatments, without reflecting the diversity and
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Afschrift. All project members are embedded in the Section of Biomechanics of the Department of Human Movement Sciences at the Vrije Universiteit Amsterdam. This section works on a wide range of topics in