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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
, and public service. Position Summary Develop highly curated datasets of chemical bioactivity and build statistically validated and externally predictive machine learning models of these activities
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. Applicants with a knowledge base in Vibrio biology would be preferred. Minimum Education and/or Work Experience M.D. or PhD Required Qualifications Ph.D. Certificates/Credentials/Licenses PhD. Computer Skills
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(required at time of application) PhD or equivalent international degree, or enrolled in a PhD or equivalent international degree granting program Additional qualifications (required at time of start) Ph.D
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focus on machine learning in the Stanford Center Cancer Cell Therapy at Stanford University School of Medicine. We seek a highly creative and motivated scientist to perform cutting-edge computational
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of RNA regulation during RNA synthesis and how these may be disrupted in disease, utilizing high-throughput experiments and machine learning. We are looking for a motivated, hard-working individual to join
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to learn and lead exciting research projects that blend methods in pharmacoepidemiology with Artificial intelligence (AI)/Machine learning (ML) techniques to generate real-world evidence on the use
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and Fluidigm technologies at UTHSC. Qualifications PhD in Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, or a related field. Strong background in machine learning, data
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Job Description Required Qualifications: (as evidenced by an attached resume) PhD (or foreign equivalent) in Biomedical Engineering, Medical Physics, Electrical, Computer Engineering or a closely
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on the hiring manager’s preferences and should include things that can be learned or trained for. Preferred Schedule: Position Requirements: Minimum Qualifications: Minimum education: PhD in a scientific field or
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) PhD (or foreign equivalent) in Biomedical Engineering, Medical Physics, Electrical, Computer Engineering or a