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Field
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development and application of data processing workflows, working closely with existing team members across optical, infrasound and RF sensing to contribute to a genuinely multi-modal picture of atmospheric
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, four years with both research and other career-promoting work, og six years with research duties in 50% part-time position. This will be clarified in the recruitment process. A career plan will be
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will learn how to use and maintain specialized equipment for measuring gas exchange and collecting image-based and spectral data used to evaluate plant performance and stress responses. You will also
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techniques including patch clamp electrophysiology, confocal and two-photon imaging, molecular biology and biochemistry, and behavioral assays. Purpose To provide research support in the lab of Dr. Amy Lee
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-disciplinary team of researchers, including bioinformaticians, pathologists, oncologists, and computer scientists, and conduct original research on computational pathology. Digital pathology images contain rich
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Center for Devices and Radiological Health (CDRH) | Silver Spring, Maryland | United States | about 20 hours ago
designing, implementing, and optimizing computational pathology workflows from image acquisition through analysis output with understanding pre-processing techniques Learn about cutting-edge vision and
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the nonlinear Hall effect, could potentially explain the observed experimental OR current. Using experimental probes such as x-ray and other material analysis techniques, imaging, probe-based microscopy, visible
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headquarters in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You can find more information about working at NTNU and the application process here
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Center for Drug Evaluation and Research (CDER) | Jefferson, Arkansas | United States | about 2 months ago
(CDER) performs an essential public health task by making sure that safe and effective drugs are available to improve the health of people in the United States. As part of the U.S. Food and Drug
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-Informed Neural Networks (PINNs) and hybrid models that respect the physical laws governing the real-world system Applying Deep Reinforcement Learning (DRL) algorithms to optimize processes within simulation