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Europe in electrochemistry, energy storage, power electronics, process engineering, smart sensors, IoT, and solar power. Together, we pursue the common goal of accelerating the decarbonization of energy
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to assess stakeholder needs, create PV-integrated sensors to monitor agriculture-specific stressors, model stress impacts on PV performance, and develop innovative PV tracker controls. These elements will be
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spatial variability of soil health. You will be contributing to specifically the area of using proximal and remote sensors, soil physical, chemical and biological data, as well as plant and weather data
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sciences or environmental engineering/ sensor techniques including remote sensing, or similar, 5+ years following PhD, Proficient programming skills, with a background in using and processing complex land
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twinning for production and process optimization. A first-of-its-kind pilot factory is now based at Aarhus University (AU Viborg), and has been equipped with about 200 sensors and a production management
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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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scientists and patient groups. This gives access to MINDLab Core Experimental Facility with an impressive infrastructure providing an array of state-of-the-art technologies (PET, MRI, fMRI, MEG, EEG, tDCS, and