8 condition-monitoring-machine-learning Postdoctoral positions at Texas A&M AgriLife Extension
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deployment. Experience with reinforcement learning (RL), computer vision, and sim-to-real transfer. Experience with robotic hardware platforms such as mobile robots, robotic arms, and embedded sensors
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networks; experience in applying machine learning models and processing imagery from UAS and satellite platforms. Other Requirements: Willingness to work irregular hours and in occasionally adverse weather
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monitoring and modeling across various freshwater systems. Compile and critically review the current state of knowledge on N2O emissions and modeling in freshwater ecosystems. Acquire, organize, and analyze
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AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about how you can be a part of AgriLife and
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networks; experience in applying machine learning models and processing imagery from UAS and satellite platforms. Other requirements: Willingness to work irregular hours and in occasionally adverse weather
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Knowledge, Skills and Abilities: Good computer and communication skills. Ability to multi task and work cooperatively with others. Preferred Knowledge, Skills and Abilities: Knowledge of crop physiology and
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AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about how you can be a part of AgriLife and
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molecular compounds that comprise phytonutrients using metabolomics, ionomics, genomics, and molecular biology. Conduct studies of plant growth in greenhouse and field conditions. Conduct wet-lab methods