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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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develop novel computational approaches. Develop mathematical descriptions for the acquired data and work with our theorists collaborators to implement new theories. Integrate with the rest of the lab and
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Duke University, Department of Mathematics Position ID: Duke -Math -POSTDOCASSOC [#30408] Position Title: Position Type: Postdoctoral Position Location: Durham, North Carolina 27708
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, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control
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mathematics and engineering. The Interpretable Machine Learning Lab has dedicated access to high-performance CPU and GPU computing resources provided by Duke University’s Research Computing unit and state
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theory, multi-objective optimization and machine learning. The specific project aims to understand the multiscale interactions shaping human gut bacteria and human gut pathogens. The project will combine
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, Bioengineering, Biophysics, Biostatistics, Mathematics, Statistics, Electrical Engineering, Biomedical data science, etc; Candidates with multidisciplinary backgrounds are also welcome. Strong skills in
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genomics, metabolomics, or microbiome analysis Computer science, particularly machine learning, artificial intelligence, data science, or computational biology Mathematics or statistics, with experience in