81 deep-learning-phd-"Computer-Vision-Center" Postdoctoral positions at Rutgers University
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Minimum Education and Experience The candidate must hold a PhD in the fields of Neuroscience, Cell Biology, Biological Sciences, or closely related fields, and must have a strong background in cell
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Minimum qualifications include a PhD in quantitative ecology, fisheries, statistics, applied mathematics, theoretical ecology, or a related field. Certifications/Licenses Required Knowledge, Skills, and
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Minimum qualifications include a PhD in quantitative ecology, fisheries, statistics, applied mathematics, theoretical ecology, or a related field. Certifications/Licenses Required Knowledge, Skills, and
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Qualifications Minimum Education and Experience A Ph.D. in Neuroscience, Molecular Biology, Genetics, or a related field. Certifications/Licenses Required Knowledge, Skills, and Abilities PhD in Neuroscience is
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well as leading efforts in mutual learning among researchers, practitioners, advocates, community organizers, and policymakers. The Associate will conduct research in the context of research practice partnerships
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analyses or the ability to effectively learn these techniques will be needed. Effective oral and written communication skills. Preferred Qualifications Experience in immunology, T cell biology, and cancer
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Minimum Education and Experience Qualified candidate must hold a PhD degree. Candidates in ABD (all but degree) status will also be considered. Certifications/Licenses Required Knowledge, Skills, and
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virtual reality development, machine learning, or advanced data analyses and modeling are highly desirable. Position Status Full Time Posting Number 25FA0682 Posting Open Date Posting Close Date
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. The successful applicant will work in the areas of causal inference and statistical learning with high-dimensional observational data, including development of statistical and computational methods, and
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, computer vision and machine learning algorithms. · Information dissemination and decision-support services · Policy related analysis and investigation · Previous interactions with transportation funding