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Field
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unravel the complex relationships between land use changes and fire regimes over the past 60 years. The successful candidate will lead efforts to: Develop advanced deep learning algorithms for classifying
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for information and communication technologies, in particular displays, image sensors and secure communications. The main drive of the group is to carry out applied research which bridges academia and industry, by
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research studies for automated image analysis. In particular, you will: Plan, develop, and implement AI/ML algorithms for pathology image analysis. Integrate multi-modal data (e.g., genomics, clinical data
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dynamics, solid mechanics, soft matter or active matter. • To become familiar with simulation algorithms as needed, assist in the development of new ones, test and document any newly developed
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algorithms, and decision-support tool development. Responsibilities will include programming, analysing and interpreting data, and contributing to innovative solutions that support maritime decarbonisation
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together experts in systems neuroscience, AI, and engineering. This ambitious initiative promises to offer unprecedented insights into the brain's algorithms of perception and cognition while serving as a
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to enable future advanced applications of diamond electronic and quantum devices and sensors. Fundamental studies using highly controlled exposures of selected (e.g., Cl and O) neutrals and/or ions in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 6 hours ago
looking for a postdoctoral fellow interested in developing either machine learning algorithms for high-resolution histopathology imaging/spatial-profiling data in combination with other modalities (e.g
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Description The Jones Lab at Georgetown University uses innovative techniques to map greenhouse gas emissions both locally and around the world. The lab is actively engaged in sensor development, field work
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a 3-year DOE-sponsored project that started in September 2024. The Postdoctoral Research Associate working on P1 will develop and test deep learning algorithms for model emulation and model parameter