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learning objectives to fit your personal career development goals, while providing guidance and education that will prepare you for your future. Where will I be located? Natick, Massachusetts Please note
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, data engineering, data analytics, artificial intelligence, machine learning, deep learning, natural language processing, and automation using modern tools and techniques. During this fellowship, you will
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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 research in several areas. These include, but are not limited to: Adversarial location and network interdiction models Adversarial machine learning attacks and defense (e.g., against Bayesian
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well as exploring the application of research findings to advanced 3D models such as organoids and 3D bioprinted tissues Learning about high-content, automated phenotypic drug screening pipelines against high
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incorporating artificial intelligence/machine learning functions in any of the previously listed training activities. Training is approved for remote appointments. Mentor(s): The mentor for this opportunity is
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the soil-water-plant-air continuum using process-based models. You will learn how to take proper soil, plant and air samples that influence carbon and nitrogen dynamics and learns how soil and plant
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of multiple surveillance and administrative data sources. Development of reproducible analytical workflows using programming languages such as R and Python. Application of machine learning and predictive
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. This fellowship requires in-person participation in Manhattan, Kansas. Learning objectives: During this appointment, you will have the opportunity to: Gain experience in sorting and identifying insects of medical
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(ONT) and the Illumina NextSeq 1000/2000 platforms for malaria genomic testing. Learning Objectives: The laboratory is seeking a fellow for a 1-year fellowship for the following training objectives