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                healthcare. Qualifications Required: PhD (or equivalent) in computer science, statistics, biostatistics, electrical/biomedical engineering, or related quantitative field. Strong background in machine learning 
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                and mathematical modeling, hierarchical statistical modeling, machine learning, remote sensing, geospatial statistics) • Demonstrated ability to conduct independent research and publish high-quality 
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                . Minimum Requirements: PhD or equivalent doctorate (e.g., ScD, MD, DVM) in psychology, psychiatry, neuroscience, biostatistics, bioinformatics, computer science, or a related field. Research background in 
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                contributed to the identification of vaccine and therapeutic candidates currently being produced in Good Manufacturing Practice facilities for early phase clinical trials. Minimum Requirements: PhD in 
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                , including development of new computational tools for processing large-scale biospecimen data Creation of novel machine learning frameworks for automated scientific analysis and discovery Design and 
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                multiple affiliations. Be You. Minimum Requirements: The Postdoctoral Appointee holds a PhD or equivalent doctorate (e.g. ScD, MD, DVM). Candidates with non-US degrees may be required to provide proof 
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                the position is filled. REQUIRED EDUCATION AND EXPERIENCE: DEFINITION: The Postdoctoral Appointee holds a PhD or equivalent doctorate (e.g. ScD, MD, DVM). Candidates with non-US degrees may be required 
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                data, identifying structural errors in the dataset, and for maintaining a record of all steps from data extraction to dataset assembly · Fitting of machine learning models · Development of instrumental 
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                the nation. The school consists of four departments with 130 tenure-track faculty members, 1250 undergraduate students, 1400 master’s students, and 600 PhD students. Housed within a university renowned for its 
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                projects aimed at developing resource responsible, economically viable solutions to challenges in the food production and critical material systems. There will be the opportunity to mentor students, teach