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decision making, whole farm management, efficiency, productivity, profitability, and sustainability. Technologies used should include some of the following, UAS, robots, sensors, internet of things
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design, prototyping, testing, and refinement of robotic systems and automation solutions, including sensor integration and feedback control. Collaborate with a multidisciplinary team to design and execute
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, etc. -Collect crop canopy data using crop sensors . Data entry and data management: -Perform basic statistical analysis using any software. -Maintain database of weather, soil, and crop data. -Shipping
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genetic knockouts in yeast and mammalian cell lines, and protein purification. Job Responsibilities: 35%: Computational algorithm development and data analysis 35%: Design and conduct experiments with yeast
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plant physiology under controlled environments Experience using data loggers and environmental sensors for automated data acquisition, as well as conducting leaf gas exchange and chlorophyll fluorescence
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environments, and communicate fluently in English. Ability to multi-task and work cooperatively with others. Preferred Qualifications: Skills in the setup, instrumentation, and maintenance of sensors and sensor
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of agricultural water use. Specific focus areas include applying AI/ML to analyze remote sensing and sensor data for predicting crop water requirements, advancing irrigation scheduling, and supporting real-time
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data, algorithms, and models will be obtained from government, university, and industry sources, including other Blackland/Grassland team members and their collaborators nationwide and worldwide
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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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emissions and soil health parameters. Results will be published in peer-reviewed journals and technical reports, and algorithms and models will be shared with stakeholders and the scientific and forest