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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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circuitry in mediating risk for tobacco use among individuals with a history of childhood adversity. The second project, PRISM, is part of an interdisciplinary collaboration between Dr. Sweitzer and Dr
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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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, 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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prospective clinical natural history studies to better understand disease progression and clinical outcomes of patients. This postdoc will collaborate with different research team members and clinical
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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