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Field
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Responsibilities: · Design and conduct independent research projects in placental biology or in utero gene editing. · Develop and optimize CRISPR-Cas9 base editing strategies, including plasmid and
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to develop and optimize protocols for various ‘omic techniques (single cell transcriptomics, proteomics, etc.) and other techniques for assaying protein function in non-model organisms at different life stages
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Computer Science or Mathematics, ideally with a background in one or more of the following areas: Optimization, Game Theory, Machine Learning Applicants must demonstrate: • An excellent academic record, including
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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characterize polymer and dendrimer-based nanomaterials for targeted drug, and gene delivery. Develop and optimize linker chemistries and conjugation strategies for attaching therapeutics, targeting ligands, and
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CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | 3 months ago
to feed juvenile seabass in a pilot study. The most promising SCP from pilot study will undergo a validation study under EFSA recommendations with different levels of PP replacement to determine optimal
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISION Our vision is to be the nation’s leading public
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species. It can be fine-tuned for downstream applications such as predicting genetic perturbations, optimizing photosynthetic apparatus for performance, selecting top performing genotypes for various
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Nephrology. Please explore our website to learn more about our state-of-the-art clinical, educational and research programs, and distinguished faculty members. (https://medschool.cuanschutz.edu/renal ) Dr
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motion planning and control strategies for multi-robot systems. Analyzing the theoretical guarantees of these frameworks using tools from optimization, machine learning, and control theory. Developing