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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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where new health hazards (such as vapor intrusion or changes in chemical toxicity) have emerged. Learning Objectives: You will have the opportunity to: Learn ATSDR’s approach to conducting public health
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against expensive and dangerous health threats, and responds when these arise. Research Project: ATSDR Region 6 seeks to host an ORISE Fellow in Dallas, Texas. The ORISE fellow's primary learning experience
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Experience or interest in artificial intelligence (AI), machine learning, or AI-assisted workflow automation Experience with software testing, beta testing, user acceptance testing, or information system
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analysis and application of machine learning techniques to structured numerical and unstructured textual data; (d) have a good track record of academic writing, including report writing, manuscript
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anticipated to receive by July 2027. Preferred skills: Academic training in computer science, artificial intelligence or machine learning, data science, bioinformatics, computational biology, epidemiology
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and experience of protein molecular modelling, protein–ligand docking, machine learning methods for computational biology, and software development in Python. Please upload your CV (including
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the application of machine learning/artificial intelligence (ML/AI) in environmental health. This project aligns with ATSDR's current strategic initiatives and will provide you with opportunities
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presentations, technical reports, posters, abstracts, and manuscripts. Activities may be tailored your scientific background, interests, and professional development goals. Learning Objectives: During
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and capability gaps. Learning Objectives: Through this opportunity, you will gain knowledge and practical experience in biosurveillance, emerging biological threats, public health preparedness, program