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models for the integration of healthcare data specifically incorporating patient preferences. This includes challenges such as how to adapt to different perspectives and data models as well as ensuring
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to track how the prevalences of different strains in a mixed sample change over time. Your role: You will develop and implement algorithms to find, quantify and track mutations in evolving populations
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models that represent and reason about complex biological systems, enabling predictions and interventions that can alter system behaviour in desired ways. For example, why do cells respond differently
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and algorithmic foundations for goal-oriented, semantics-aware communication strategies that enable efficient, intelligent, and adaptive information exchange in joint communication and control. In
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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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. It is not feasible to scan the full volume of such samples at the highest desired resolution. Therefore, we require an imaging scheme that acquires relevant features at different length scales and
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activity to mouse behavior” (Program Coordinator Prof. Froudarakis) invites applications for one (1) motivated PhD student to assist with the understanding of the algorithm that the brain uses to identify
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. It will use signals from different sources—such as radio signals and internal sensors— to maintain robust and accurate PNT, even when satellite signals are weak or missing. A built-in intelligent
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such as how to adapt to different perspectives and data models as well as ensuring high quality and robust integration. The PhD is situated in the Intelligent Data Engineering Lab and will be supervised by
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creating robust, low cost, and real-time edge-AI algorithms capable of accurately classifying diverse marine species and debris under complex and dynamic underwater conditions. The demand for such a low-cost