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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
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research environment with a strong scientific and social network for postdoctoral fellows and good mentoring opportunities to support individual career development. You will have access to state-of-the-art
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including research management, communication, networking, writing of manuscripts etc. Mentoring and career development in a network of national and international collaborators Research exchange to
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limited to: Testing underwater frames and instrumentation, including sensor testing and calibration Quantifying benthic biogeochemical fluxes and momentum fluxes in situ from high-density datasets (e.g
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research in digital and high-frequency electronics, embedded systems, control, and communication, utilizing cutting-edge reconfigurable computing and sensors. The aim is to develop next-generation
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, for example, on elite network data, union data and measures of institutional embeddedness. The Fellow is expected to produce original research work from this data, delivering historical analysis of income
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including research management, communication, networking, writing of manuscripts etc. Mentoring and career development in a network of national and international collaborators Research exchange to
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] that trap light to reduce the number of controllable components. Our long-term goal is to develop a general-purpose PIC platform, so we welcome applicants interested in sensors, optical communications, AI
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adjustment and plate tectonics. The analysis will encompass both network wide and local analysis using data from Greenland GNSS Network (GNET). You will target specific regions where there can be an unresolved