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Field
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sensors, RGB/IR cameras, video systems, insect traps, and other devices to build predictive, AI- and machine-learning based models for monitoring grain quality and detecting deterioration due to mold
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and assessing weld quality of mechanical parts in real-time by developing machine learning models that use sensor data and other tasks that are assigned to you. Core Responsibilities: Understanding
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on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems
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, root imaging) with biogeochemical, microbial, or environmental sensor data. Experience analyzing large datasets in reproducible formats (R, etc.) Demonstrated interdisciplinary and systems-level approach
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the holistic understanding of space and its broader societal, ethical, and environmental impacts. Through responsible, multi-disciplinary research, including novel sensors, environment modelling
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flood-analysis methods. Coordinate field measurements and model validation along selected urban transects, including microclimate sensors, thermal observations, photogrammetric surveys and field
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project “Biowaste-Based Stretchable Sensor Modules for Sustainable Plant Wearables”, which aims to develop sustainable, stretchable, and biodegradable plant-wearable sensors for precision agriculture
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, wearable sensors, biosignals, and sleep physiology. Excellent problem-solving abilities, with a demonstrated capacity to contribute to cutting-edge research, secure external funding, and effectively
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the holistic understanding of space and its broader societal, ethical, and environmental impacts. Through responsible, multi-disciplinary research, including novel sensors, environment modelling
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sciences. This includes the integration of various types of field-based and sensor-based data (soil, acoustic, images, and species data), as well as historical maps and satellite- and drone-based data. By