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Field
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medicine, complex disease mechanism, systems pharmacology, bioinformatics, and network science/statistical physics. This position at Northeastern University may include opportunities to collaborate with
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About the Role The project “An Erlangen Programme for AI” (funded by the UKRI), will broadly involve applying advanced mathematical techniques for understanding training in neural networks, with
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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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on addressing the complexity of the device-software-application-data design space, enabling systematic and efficient exploration using modeling and simulation tools.## Key Responsibilities- Identify and
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emphasize the different kind or levels, known as layers, of connections between the elements of the network and the interactions between these levels as well. In order to capture the structure and complexity
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
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between Duke University and the National University of Singapore (NUS). It works closely with the Singapore Health Services (SingHealth) cluster, which is a network of national specialty disease centres
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responsible for the project Design, synthesis, and characterization of complex organic molecules which play a pivotal role in DNP, Employ advanced NMR/MRI methods for structural analysis and DNP-related studies
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Their Human Host: Networks of Interaction” (www.funginet.de ) funded by the Deutsche Forschungsgemeinschaft and the consortium SynThera funded by the Carl Zeiss Foundation (www.synthera.eu/ ). We
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learning techniques to address complex biological questions with significant societal impact. The position offers the opportunity to contribute to groundbreaking research that will advance our understanding