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of modeling higher-order relational structures such as hypergraphs and simplicial complexes, which are prevalent in complex biological systems like protein assemblies, signaling pathways, and metabolic networks
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studies, designing and implementing complex immunological assays, analyzing data from clinical cohorts, and generating impactful publications. As part of a dynamic and multicultural team of international
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- based neural networks, Bayesian statistics, and text analytics are a must. Nice to Have: Experience developing and integrating APIs for healthcare systems to ensure seamless interaction with AI models
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approaches to assessing the human pancreas, including live pancreas slice methodologies that may include cellular imaging or labelling approaches Leveraging complex multi-modal phenotyping data to develop new
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of Luxembourg, the Greater Region, and beyond. Nearly all research projects are supported by a network of national and international partnerships, several with public or industrial stakeholders. At the University
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activities towards quantum information systems. Use cases of interest include IoT verticals, unmanned aerial vehicles, integrated satellite-space-terrestrial networks, quantum communications and key
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the approximation over time, (2) Energy-based optimization that balances accuracy and mesh complexity, or (3) Graph-based techniques that seek near-optimal connectivity structures for mesh representation. • Recent
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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
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of seed gene networks”. This project aims to use reverse genetics, cross-species complementation and single cell next-generation sequencing approaches to investigate how the gene networks that regulate
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renewable, benefits-eligible position. The University of Chicago Knowledge Lab leverages advanced computational tools to unravel complex scientific and societal problems, bridging the gap between data-driven