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, Physics , quant-ph , Quantum Science + Quantum Information Science + Quantum Optics + Theoretical Physics , Quantum Sensors , Theoretical Particle Physics , Theoretical Physics, HEP-Phenomenology (hep-ph
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
focused on environmental applications for air quality management. This will include acquiring datasets related to multiple air quality sensors from diverse data sources, develop open-source, easy to use
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, including renewable energy sources and energy storage systems.Development of predictive models and soft sensors for monitoring the technical condition and operational parameters of energy infrastructure (e.g
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. Preferred Qualifications Experience with energy and air quality sensor technology, data, and modeling platforms. Equipment Utilized Software Skills: Most or all: R, STATA, Python, MATLAB, SQL, ArcGIS, QGIS
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of Norway through the “Arctic MSCA-PF program”. Successful postdoc candidates will be invited for a two-day MSCA-PF symposium June 10-11, 2026 (hybrid physical/digital event, see details at https://uit.no
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of novel and autonomous marine monitoring technologies (gliders, micro-AUVs, buoy stations with fixed and profiling sensors). Designing and organizing oceanographic experiments. Implementing autonomous
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maintain end-to-end EO data processing pipelines, from sensor calibration to the extraction of geophysical variables. Implement machine learning and image processing techniques to fuse optical and SAR data
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French National Research Institute for Agriculture, Food, and the Environment (INRAE) | Avignon, Provence Alpes Cote d Azur | France | 3 months ago
capacity. You can take advantage of the current dynamic around sensors at PSH to strengthen existing collaborations, especially with the EMMAH unit for the use of proxy or remote sensing tools (for example
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or predictive modelling, edge AI, AI for biomaterials formulation, processing and manufacturing optimization. Wearable devices – wearable physiological sensors, smart textiles, soft robotics, and exoskeletons
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trained in and ultimately read and interpret proprietary building automation system dashboards (e.g. Johnson Controls), respond to equipment sensors and alarms that send data and readings to a dashboard