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the technical side, we aim at combining statistical latent variable models with deep learning algorithms to justify existing results and allow a better understanding of their performances and their limitations
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implementing new informatics tools and resources to enhance phenotyping performance or enable deep phenotyping through terminology/ontology, natural language processing, and machine learning. The role involves
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research work will be to devise efficient algorithms for source separation in DAS measurements. Issues such as large data volumes that can exceed 1 To per day and per fiber, instrument noise, complex nature
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for Humanity. What you would be doing: Research – As a part of the Dyson School of Design Engineering, you will actively develop and lead your own research programme, in line with our research themes and vision
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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analyzed. The tensor model structure estimated by suitable optimization algorithms, such as that recently developed in [GOU20], will be considered as a starting point. • Exploiting data multimodality and
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algorithms, clinical decision support systems, and population health management platforms. Evaluate emerging technologies in clinical informatics and provide strategic recommendations for their adoption within
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manner. Collaborative Innovation: Lead and participate in collaborative initiatives aimed at developing novel computational tools, algorithms, and models that address critical challenges in drug discovery
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learning, new algorithms, and AI for Science. The graduate program at CMLR is an interdisciplinary, international program aimed at producing the best talents at the frontier of all disciplines where machine
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, differential geometry, partial differential equations, number theory, probability. Theory of Computing: all areas of theoretical computer science, especially algorithms and computa- tional complexity. Applied