14 phd-computer "https:" Fellowship positions at Northeastern University in United States
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. Additional expectations include recruiting and mentoring PhD students, directing their own research program, serving on external program committees, and building collaborative relationships with industry
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About the Opportunity About the Opportunity Northeastern University Pharmaceutical Industry Fellowships Program is a two-year experiential program designed to advance lifelong learning and the
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Ph.D. in any aspects of climate and/or sustainability, with either by a PhD degree in any aspect of climate and/or sustainability sciences and engineering (e.g., to coincide with one of the five themes
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the following training will be considered PhD in computer science, machine learning, AI or related computational field, or, Ph.D. in a health-related discipline with experience in experimental science, devices
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interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and functional neuroimaging data. Specific activities may include
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Number: 6821498 Takeda-Global Medical Affairs Postdoctoral Research Fellow About the Opportunity About the Opportunity Northeastern University Pharmaceutical Industry Fellowships Program is a two-year
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Number: 6821503 Takeda-Global Regulatory Affairs Postdoctoral Research Fellow About the Opportunity About the Opportunity Northeastern University Pharmaceutical Industry Fellowships Program is a two-year
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Number: 6791163 Takeda-Global Medical Affairs Postdoctoral Research Fellow About the Opportunity About the Opportunity Northeastern University Pharmaceutical Industry Fellowships Program is a two-year
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Number: 6791168 Takeda-Global Regulatory Affairs Postdoctoral Research Fellow About the Opportunity About the Opportunity Northeastern University Pharmaceutical Industry Fellowships Program is a two-year
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factors. Though not required, we are particularly interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and