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computational process that takes place in brains or computers. Yet many physical systems, from biological networks to adaptive materials, continuously modify their behavior based on past experience
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pollinate. Bayesian networks (BNs), and other probabilistic graphical models, can provide a visual representation of the underlying structure of a complex system by representing domain experts’ beliefs
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pollinate. Bayesian networks (BNs), and other probabilistic graphical models, can provide a visual representation of the underlying structure of a complex system by representing domain experts’ beliefs
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complex, structured data, with a focus on graphs. It will investigate methodological improvements to Graph Neural Networks (or related models), based on Network Science and structural properties of the
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• Bachelors degree in Information Technology, Computer Science, Engineering, or a related field or experience. • Minimum of five (5) years of experience in IT management, involving complex networks and
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-order spreading” and 2.3 “Higher-order evolutionary processes”), aims to develop theoretical and computational models for the study of dynamical processes on networks with higher-order interactions. By
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Director will serve as a primary architect of the Center’s external presence and intellectual impact, building the partnerships, networks, and flagship initiatives through which that mission becomes
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essential for conserving biodiversity and supporting resilient ecosystems in a changing world. Ecosystems can be described as complex networks of interacting species. DC1 will investigate how the
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Communications & Applications: - Provide technical oversight for a complex enterprise communications architecture supporting 6,000+ endpoints, 120 emergency response systems, and high-volume call centers across
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develop new methods and tools for gene regulatory networks, single-cell multi-omics integration, spatial omics, and variant effect mapping in complex disease. Strong method/tool dev experience required