120 parallel-computing-numerical-methods Postdoctoral positions at Rutgers University
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policy analysis approaches and methods, including stakeholder interest and conflict analysis, benefit-cost analysis, utility rate development, program evaluation, regulatory policy analysis and report
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Investigator neuroimaging research projects; contributes to meeting regulatory compliance (IRB and possible IACUC) and to the compilation of regulatory protocols; designs, tests and evaluates methods and
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he successful candidate is expected to have experience with advanced functional neuroimaging data analysis methods and/or computational cognitive modeling. Preferred Qualifications Previous experience
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. This postdoctoral associate position will be housed in the Department of Plant Biology at Rutgers University, New Jersey in Vaccinium breeding program of Dr. Gina Sideli. This position will also work with Rutgers and
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opportunity to contribute to cutting-edge research in the development of clinical trials, self-management science, acute/chronic disease management and pain mechanisms and methods under the mentorship
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renewable for two additional years pending productivity, performance, and overall fit. The postdoctoral program enables associates to build a high caliber scholarly portfolio in LGBTQ+ public health research
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to work independently; • Experience working on research projects with a research team; and • Excellent verbal, writing and analytical, organizational and attention to detail skills, computer literacy and
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-infiltrating lymphocytes and gene-engineered T cells. Postdoctoral Associates are expected to establish an innovative, collaborative research program addressing important and fundamental questions. Active areas
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span a broad range of areas including strongly correlated fermion materials, high-temperature superconductivity, topological electronic states of matter, developments and applications of computational
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lead research projects to investigate how bioactive lipids and other related bioactive compounds influence chronic diseases using advanced analytical techniques and statistical methods under Dr. Liang’s