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to, generating synthetic social networks to describe transmission using latent space models, organizing and extending extant network data models, and building Agent Based Models of multi-state disease and behavior
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Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks (PINNs), Biologically Informed Neural Networks (BINNs), and
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application to medical imaging (e.g., MRI) · Experience with MRI data analysis, network science, graph theory, topological analysis, or related computational approaches, especially in Alzheimer’s
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infrastructure, mobility, and socio-economic networks influence malaria transmission across border communities; and (iii) Collaborate with public health authorities and community partners to apply findings
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number of projects involving large complexes involved in protein-nucleic acid processes, with a particular focus on proteins and complexes important in microbial pathogenesis. Specific responsibilities
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, predictive assembly of complex microbial communities, and programming of self-organized pattern formation in engineered bacteria. Duke is an Equal Opportunity Employer committed to providing employment
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interpretable deep neural networks is required. Candidate must have published in top journal and conference at least one scientific paper in interpretable machine learning (not explanations of black boxes) among
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therapeutics will be tested in these models, such as vagus nerve stimulation and anti-inflammatory compounds. Some of these scientific questions will further address the complexity of innate immune signaling
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, Pratt prepares future engineering leaders to address complex challenges with solutions that take into account the complexities and nuances of implementing them. Pratt takes a whole-student approach to
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polyfluoroalkyl substances (PFAS) in North Carolina, the International Network For Researching, Advancing, and Assessing Materials for Environmental Sustainability (INFRAMES), and more. Our location in