149 web-programmer-developer-"St"-"UCL"-"St" Postdoctoral positions at Rutgers University
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role of a successful candidate will be to develop compositions and processing of these resins that will enable high performance energetics with tunable mechanical properties. Dr. Singer’s lab, the Hybrid
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conduct independently or as assigned specialized research for a particular project. Participates in the development of performance standards, selection of methodology and instrumentation and coordination
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conduct independently or as assigned specialized research for a particular project. Participates in the development of performance standards, selection of methodology and instrumentation and coordination
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productivity, performance, and overall fit. The postdoctoral program enables associates to build a high caliber scholarly portfolio in social-structural determinants of health, intersectionality, and community
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of findings. The research program is focused on understanding the role of extracellular vesicles and steroid hormones during pregnancy in shaping brain development and behavior. The Postdoc is expected
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of the Postdoctoral Associate position is to conduct independent laboratory research under the direction of the Principal Investigator. The research interest of the Feng lab is to study the development and progression
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your technical and conceptual training, mentorship, and career development. It is an excellent opportunity for neuroscientists looking to advance their training in next-generation in-vivo approaches
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operations, including breeding and genotyping of mice and general maintenance of animal colonies. Develops new ideas for promotion current research for the NJMS –Center for Immunity and Inflammation. Operates
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Demands and Work Environment Overview Level of decision making: Application materials, interview, and presentation. Scoore and Impact: Research Program and project Statement Posting Details Special
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have the opportunity to develop independent research aligned with the aims of the ADN lab. Current work focuses on machine learning and multivariate decoding of neuroimaging data to predict subjective