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uncertainty quantification into scientific machine learning workflows and optimize the design of computational (ABM) and wet-lab experiments. • Collaborate with mathematical modelers and experimentalists in
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available in the Center for the Chemistry of Molecularly Optimized Networks (MONET) at Duke University. The position will support the development and use of data tools for polymer network chemistry, lead and
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Postdoctoral Associates. Scope of Work: • Lead the design and synthesis of novel chemical entities. • Optimize reaction conditions and processes for the synthesis of lead compounds. • Perform detailed analysis
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stochastic models from ABM simulations and multiscale spatial-omics data. • Integrate uncertainty quantification into scientific machine learning workflows and optimize the design of computational (ABM) and