13 machine-learning-modeling Postdoctoral positions at Duke University in United States
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models that include these mechanisms. The postdoc will develop biologically-constrained machine learning–based model discovery pipelines to derive interpretable surrogate ODE/PDE models from simulated ABM
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biologically-constrained machine learning–based model discovery pipelines to derive interpretable surrogate ODE/PDE models from simulated ABM data and spatial-omics data collected from state-of-the-art
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and as part of a collaborative, interdisciplinary team. Commitment to publishing research and pursuing a career in academic or translational research. Experience with statistical modeling, machine
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and mathematical modeling, hierarchical statistical modeling, machine learning, remote sensing, geospatial statistics) • Demonstrated ability to conduct independent research and publish high-quality
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able to manage multiple and rapidly changing priorities and have ability to quickly learn new skills. Must be detail-oriented, well organized with strong communication skills and ability to work in an
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policies pertaining to other schools at Duke University. The postdoc candidate is expected to: 1) Develop novel methods for incorporating scientific machine learning in solving problems in solid mechanics
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data, identifying structural errors in the dataset, and for maintaining a record of all steps from data extraction to dataset assembly · Fitting of machine learning models · Development of instrumental
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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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conduct policies about other schools at Duke University. Compliance with all applicable University and departmental policies and procedures. The postdoc candidate is expected to: 1)Development of machine
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, establishment of a seagrass farm, and monitoring of a large living shoreline project. In addition to research, the post-doctoral scholar will be required to teach a 4-5 week-long field course each spring semester