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and field monitoring work performed by a PhD student at LIST and other researchers in LAFI, and extend the existing Vegetation Optimality Model (VOM, https://vom.readthedocs.io ) to test the following
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differentiation of brain, gut, and placenta organoids, as well as optimizing robust protocols that form the experimental foundation of the laboratory's research program. Who are you? To be employed as a
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, synthesis, and optimization of organic, inorganic, and composite coatings Implementation and optimization of plasma deposition processes at low pressure and atmospheric pressure Characterization of
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direction and publication. Research activities may include AI-assisted target discovery and biologic design, protein engineering and developability optimization, mechanistic studies in metabolic disease
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focused on translational control in cancer • Drive the development and advance our single-cell ribosome profiling strategies in mouse models of cancer • Contribute to the development and optimization of new
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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optimize chemical compounds. Your work relies heavily on the ability to synthesize complex chemical structures and to investigate and understand chemical-physical and biological properties of chemical
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collaborative environment with projects and interactions spanning multiple labs within the group, across NIST and externally. Candidates should have a PhD in physics, electrical engineering, mechanical
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hydrate–based carbon capture. The work will include reaction optimization, purification strategy development, scale-up toward bulk production, and exploration of alternative promoter candidates
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to predict bacterial growth from protein sequence and compound molecular structure. Applying generative and predictive models to propose novel compounds optimized for broad-spectrum activity against diverse