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motivated individuals to join our dynamic team as Postdoctoral Associates. Scope of Work: • Lead the design and synthesis of novel chemical entities. • Optimize reaction conditions and processes
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simulations and multiscale spatial-omics data. • Integrate uncertainty quantification into scientific machine learning workflows and optimize the design of computational (ABM) and wet-lab experiments
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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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of the mass spectrometry-based proteomic data generated in our chemoproteomics experiments. The postdoctoral associate will be responsible for developing and optimizing custom data analysis and visualization
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Bioinformatics expertise required for scRNAseq analysis. · Previous cell culture experience. · Perform molecular, cellular, biochemical and immunological analyses. · Optimize and troubleshoot experimental
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-performance computing. Additional experience in DNA biophysics, machine learning, and optimization is preferred. This job description intends to provide a representative and level of the types of duties and
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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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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