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. Experience working with rodent models. Experience with mammalian cell culture. Experience with live-cell or in vivo microscopy. The optimal candidate will have a background in neuroscience or cell biology, as
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, with a focus on arboviral diseases (e.g., dengue or Oropouche viruses). Other projects include improving risk assessment, optimizing surveillance system design, and developing and evaluating mitigation
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on Compact Manifolds with Novel Feedback Coupling and Complex Network Optimization." Specifically, the selected candidate will address Research Objective (RO) (2) Investigate the dynamical phenomena of orbital
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development of novel traits. The successful candidate will be expected to develop and optimize protocols for various ‘omic techniques (single cell transcriptomics, proteomics, etc.) and other techniques
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, biologists, and data scientists. The emphasis will be on enabling high-fidelity image reconstructions from sparse and noisy data, leveraging state-of-the-art methods in compressed sensing, optimization, and
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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patient-specific, predictive models using real-world clinical data. The project aims to enhance understanding of disease trajectories, optimize treatment strategies, and support real-time clinical decision
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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 5 hours ago
, and create personal 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
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Department of Chemical and Biological Engineering at Princeton University. The position is in the broad area of renewable energy systems synthesis, analysis, and optimization. The goal of the project is to