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applications in thermal management, imaging, and sensing. You will combine nanoscale energy transport, nanofabrication, and nanophotonics expertise with collaborative skills to innovate at the intersection
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on the scientific potential/achievement of the candidates, technical experience/expertise in developing an imaging data-processing pipeline would be highly desirable. We are especially interested in candidates
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will image them using a variety of microscopy methods, and collaborate with a team of computer vision scientists to build ML-based models for phenotype prediction, helping to accelerate the cell
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will support the implementation of the project. These activities include acquiring and analyzing behavioral and brain imaging data from vision science experiments, with an emphasis on discovering and
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cell lines have been engineered and characterised, you will image them using a variety of microscopy methods, and collaborate with a team of computer vision scientists to build ML-based models
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will assume a lead role in developing stabilized microbubble conjugates for delivery of neurotransmitters and therapeutics for brain imaging and delivery technology. The project will take advantage
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strong background in machine learning, computer vision, or data-driven modeling. You have extensive experience in the development and implementation of AI and machine learning algorithms, ideally with
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at the Division of Materials and Manufacture, which belong to the Department of Industrial and Materials Science. The Department of Industrial and Materials Science shares knowledge and their vision of technical
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initiation, progression, therapy response and prognosis, and (iv) novel microbe discovery in cancer and other chronic diseases. The knowledge gained using our “tumor ecology” paradigm will be translated
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Mississippi. Apply computer vision and machine learning approaches to integrate ground-based imagery, remote sensing data, and lidar data for high-resolution flood detection and mapping. Develop and calibrate