65 phd-mathematical-modelling-population-modelling Postdoctoral positions at Duke University
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recent Ph.D. in microbiology, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative
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restoration of function. The successful applicant will combine computational modeling, engineering optimization, and in vivo experiments to advance understanding and application of electrical block of neural
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to advance the application of computational hemodynamic models of cardiovascular flow to aid in remote tracking and early diagnosis of disease. The applicant will gain exposure to other projects in the lab
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the vagal complex with multiple imaging modalities, spanning gross anatomy to nerve morphology to microscopy resolving individual neurons. These imaging data provide inputs to computational models
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pathways and mechanisms underlying autoimmunity from a lncRNA and epigenetic gene regulation perspective. We utilize biochemical assays, tissue culture, mouse transplantation & disease modeling experiments
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system. For the meta-analysis project, Bayesian background with experience in hierarchical modelling and mixed effect models is preferred. The second project, knowledge in survival analysis and machine
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tools, high-throughput screening, and human induced pluripotent stem cells (hiPSCs) to model different cell types, phenotypes, and disorders. We are looking for a highly motivated and talented candidate
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basic research and animal models, preferably rodents. The ideal candidate will have a strong background and experience in the field of neuroscience and behavior in rodent models, such as social behavior
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-analysis project, Bayesian background with experience in hierarchical modelling and mixed effect models is preferred. The second project, knowledge in survival analysis and machine learning is desired
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website. TERM One year, with the possibility of another year extension depending on successful progress. QUALIFICATIONS Applicants should hold a PhD in Earth Science, Environmental Science, or a related