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Field
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research section comprised of over 50 members dedicated to advancing micro- and nanotechnology-based sensors, detection systems, and drug-delivery devices. If you are a highly motivated individual with
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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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to enable microbial species detection and recognition in situ, using a sensor system that will eventually be deployed in agricultural fields for soil monitoring in space and time. Work duties The main duties
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will contribute to attracting national and international research funding. You will assist in the supervision of PhD students and other team members. If necessary, you will fulfill a limited number of
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 8 hours ago
from multiple methods and developing cross-sensor capabilities (e.g., combining SAR and hyperspectral) will be essential for deriving meaningful insights for biodiversity and ecological conservation
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to the in-situ field measurements at Itatinga. The Ecotron experiments are not part of the postdoctoral work and will be made by a French PhD student. Combining data from Eucalyptus stands and
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protected and open field cultivation systems Use lab and field equipment (ICP, HPLC, gas exchange analyzer, soil/root/plant sensors, chlorophyll fluorescence, etc.), data loggers and image processing tools
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on two core but complementary areas: Computer vision and sensor data analysis, applied to tasks such as object detection in drone images (e.g., pest or disease detection), object tracking (e.g. leaves
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 3 months ago
the combination of socioeconomic data and geospatial information. Experience with the calibration and deployment of low-cost sensors is preferred. Occasional travel may be necessary. Field of Science: Earth