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Field
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RAP opportunity at National Institute of Standards and Technology NIST Applications of Computational Optical Imaging Methods Location Physical Measurement Laboratory, Sensor Science Division
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smart electrical grid that increasingly relies on the use of intermittent renewable energy sources. Modern integrated building automation and control systems create an environment rich with sensor data
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. The postdoc will develop machine learning algorithms to analyze phenotype and sequence data, as well as active learning algorithms to optimize and control experiments in directed evolution. This position
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, but also in traffic monitoring or in the media context, for example when it comes to automatic metadata extraction and audio manipulation detection. Another focus is the development of algorithms
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validating science algorithms, post-flight calibration and validation, developing field observation databases, science data product development and the fusion of multi-sensor data. There is also the
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to the road? Then this position is just right for you! About us In the Autonomous Vehicle Lab, we develop the vehicle of the future with intelligent algorithms and methods. We are involved in numerous projects
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compressed sensing) to determine greenhouse gas and pollutant emissions in cities using atmospheric measurements (MUCCnet: https://atmosphere.ei.tum.de/ ) and in-situ sensor networks in ICOS Cities project
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be achieved, for example, by developing learning algorithms and bringing together different sensor systems in the vehicle and on the road. Where you put the focus - that is up to you. The concepts
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thawing, sea level budget, climate and earth system modeling, soil parameter mapping, and multi-sensor segmentation, together with our partners at renowned international and national institutes such as Bonn
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the development of image/signal processing algorithms from a multidisciplinary approach, to include multiple sensor modalities. These multidisciplinary research opportunities incorporate theoretical and