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Youssef. We are particularly interested in candidates with a strong mathematical background and expertise in one or more of the following areas: High-dimensional probability and concentration/functional
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on cutting-edge research at the intersection of statistical modeling, artificial intelligence, and infectious disease epidemiology. This position focuses on developing and applying statistical, mathematical
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Interdisciplinary Training in Mathematics for Human Health,” supported by the National Science Foundation. RTG themes include modeling in cancer biology, computational neuroscience, and mathematical epidemiology
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About the Opportunity Job Summary The Copos Group works on computational and mathematical theoretical models with direct applications to several open problems in cell biology. We are specifically
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relevant programming languages. Ability to use/learn several advanced modeling methods (e.g., statistical, mathematical, individual-based, or machine learning models). Experience with high-performance
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relevant programming languages. Ability to use/learn several advanced modeling methods (e.g., statistical, mathematical, individual-based, or machine learning models). Experience with high-performance
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in the Mathematical Institute (https://www.maths.ox.ac.uk/groups/mathematical-biology/infectious-disease-modelling ). The postdoctoral researchers will develop data-driven mathematical models and
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, transportation systems and biological interactions. These systems are represented as networks. A network is a set of objects that are connected to each other in some fashion. Mathematically, a network is
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). The research project will develop a reliable framework to accelerate the development of novel high-power particle-production target material for advanced particle accelerator applications. A reverse modeling
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the project include mathematical derivation, analysis, and comparison of models, methods, and simulation approaches; rapid prototyping of new ideas in custom code; implementation of new models, methods, and