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Details Title Postdoctoral Fellow in Riemannian Optimization School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position Description A postdoctoral position is
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perturbation screens with high content molecular and imaging data to understand cellular and multi cellular combinatorial programs in cells and tissues in health and disease. You will join a highly collaborative
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other associates to develop optimized photonic test structures that will be incorporated in PIC process flows and enable extraction of key physical parameters associated with PIC performance, including
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-affiliated hospitals. Responsibilities Design and optimize new CAR constructs and delivery systems Conduct in vitro assays to evaluate cytotoxicity, cytokine production, and phenotype Perform in vivo efficacy
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. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences. This is a one-year position with
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stabilizers and targeting motifs for delivery and persistence of activity in the brain-tumor microenvironment. · Formulate and optimize liposomes and polymeric/hybrid nanoparticles for delivery across
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synthetic chemistry and reaction optimization. A working knowledge of molecular biology and/or protein generation. For information about the (lab) at Genentech and publications, please go to: https
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such as system usability, improved patient outcomes, and workflow optimization. Preference will be given to candidates who have completed a clinical informatics fellowship or similar advanced degree
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Apply Now Job Summary In this position, the candidates will learn strategies and techniques for LC-MS analysis, drug optimization and lead drug candidate selection, pharmacokinetics and drug
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of reagents and supplies; optimize ordering and project scheduling to meet service expectations. Monitor instrument performance, oversee routine maintenance, and coordinate vendor support. Uphold SOPs, aseptic