83 postdoc-parallel-computing Postdoctoral positions at Rutgers University in United States
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to oversee research activities outlined in NSF Grant 2520154 “Understanding Expectation-Driven Learning in Early Childhood: An Experimental and Computational Investigation,” under the supervision of Dr. Kimele
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Qualifications Experience in quantitative modeling, stock assessment, population dynamics, statistics, and computer programming (R, Python, Matlab, Template Model Builder, AD Model Builder) are preferred
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Experience · PhD in oceanography, atmospheric science, geophysics, economics, computer science, statistics, or a related discipline at time of appointment; · Familiarity with literature relevant to sea-level
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Effective spoken and written English required. High level of computer literacy required. The individual must be able to navigate the highly complex and often unpredictable nature of scientific research, as
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, on program implementation and outcomes, along with producing peer-reviewed publications and public reports. The Associate will also lead the coordination of statewide and local research and practice learning
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, on program implementation and outcomes, along with producing peer-reviewed publications and public reports. The Associate will also lead the coordination of statewide and local research and practice learning
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Center of Excellence for Rapid Surveillance of Tobacco, the Tobacco Dependence Program, a Tobacco Industry Marketing Program, and a Tobacco Control Law & Policy Resource Center. Posting Summary Rutgers is
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Laboratory environment. Universal precautions are mandatory. Physical Demands and Work Environment Ability to use computing resources. Overview Statement Rutgers, The State University of New Jersey, is an
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Pension Eligibility ABP Qualifications Minimum Education and Experience PhD in biomechanics, kinesiology, biomedical engineering, computer science, or a closely related discipline. Experience with motion
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, the Postdoctoral Associate will investigate hippocampal and cortical circuits during navigation and goal-directed behaviors using large-scale electrophysiology, in vivo imaging, optogenetics, and computational