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, chromatin profiling, genomics, spatial transcriptomics and single-cell data. Apply statistical, machine learning, and network-based approaches to analyze high-dimensional biological data. Collaborate closely
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Center for Biologics Evaluation and Research (CBER) | Southern Md Facility, Maryland | United States | about 23 hours ago
are held in zoos, research facilities, venom producing facilities, and by private individuals. Exotic antivenoms are also acquired by US military for treatment of personnel positioned in other nations
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& Amputation Center of Excellence (EACE) is a unique organization within the Department of War (DoW) consisting of teams of researchers embedded at the point of care within multiple Military Treatment Facilities
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pathophysiological mechanisms for acute organ injury research under POI-KB. · Authorship of high-impact first-author or co-author manuscripts in leading informatics and machine learning journals and conferences
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for relevant systems of EF-hand proteins · Supervise and instruct graduate and undergraduate students in Dr. Pengfei Li’s lab Minimum Education and/or Work Experience A MD or PhD is required in a closely related
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to regulatory agencies, investors, pharma companies etc. Learn more about the innovative work led by Dr. Don Ingber here: https://wyss.harvard.edu/technology/human-organs-on-chips/ What you’ll do: Develop models
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to the preparation for a career in research or academia, participate in the University’s Individual Development Plan policy for postdoctoral scholars, have a PhD or equivalent terminal degree (such as MD, DVM, PsyD
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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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dataset analysis, machine learning tools, and relevant computational biology approaches • Document, compile, and format data analysis in presentations and reports to supervisor. • Mentors and trains
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preferred skill, including GIS, spatial suitability modeling, multi-criteria decision methods, and machine-learning-based feature importance. Exposure to resource questions relevant to large-load development