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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
Experience Requirements The post-doctoral fellow will have received a PhD, DrPH, MD, or equivalent doctoral degree with experience in environmental health, environmental chemistry, environmental engineering
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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students. The required qualifications are: PhD degree in mathematics, science, engineering, or a related field by the start date. Extensive experience in one or more of the following areas: probabilistic
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, performing, analyzing, and writing up to report for publication behavioral neuroscience experiments addressing questions of decision-making in rodents Qualifications Required Qualifications: PhD in
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inference attacks, to mitigate privacy leaks in MMFM. You will hold a PhD/DPhil (or be near completion) in a relevant discipline such as computer science, data science, statistics or mathematics; expertise in
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New Jersey Institute of Technology, Mathematical Sciences Position ID: 965 -POSTDOC8214 [#26824, req8214] Position Title: Position Type: Postdoctoral Position Location: Newark, New Jersey 07102
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of virus evolution into mathematical models of spillover infection and transmission of prototype viruses representing viral families concern to support the development of methods for virus sequence analysis
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guidance and support for employees, doctoral candidates and students Your Profile: Master`s degree with subsequent PhD in theoretical physics or a similar field Background and strong interest in developing
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surface properties on their energy balance and gas exchange. Experiments will be accompanied by mathematical modelling of the physical processes involved. How will you contribute? In accordance with any
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://degradationproject.com/ ) and NEXGENNa (http://nexgenna.org/ ) projects and participation in regular relevant FI meetings. Applicants should hold (or be about to obtain) a PhD in Chemistry, Materials Science, or a closely