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of the relevant fields. Degree must have been received within the past five years. Degree in instructional and game design, game theory, serious game development and simulations, interactive media or equivalent
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chronic conditions and illnesses. This research aligns with CVDB's public health mission to strengthen evidence supporting improved recognition and characterization of ME/CFS. Learning Objectives: You will
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gain valuable knowledge and skills in training machine learning models and applying Natural Language Processing (NLP) techniques such as Topic Modeling and Named Entity Recognition. Additionally, you
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learn best practices in instructional design and health communication, including web communication, application of CDC’s quality training standards, user experience, digital content design, and plain
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, alleles, variants, and genomic loci influencing disease resistance, pathogen virulence, toxin production, and host recognition. You will have the opportunity to participate in the development and
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indicators in Greater Everglades and beyond, statistical analyses for complex ecological data, and flexible, probability design creation for natural resource agencies. Project activities include, but are not
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, interpreting, and visualizing trends and patterns in complex data sets. Gaining knowledge of state-of-the-art statistical, analytical, and visualization methods and techniques through reading, meetings with
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and analyze trait measurements related to plant development, plant physiology, and seed yield under different irrigation regimes in two locations with different weather patterns. You will also aid in
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into regulatory and oversight environments. Apply STEM knowledge to educational design by learning how complex scientific and technical information can be translated into measurable learning objectives, competency
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projects, including the following diverse activities: Participating in quantitative and qualitative survey design and administration, data collection, data quality assurance processes, data management, data