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aligned with the aims of the Addiction & Decision Neuroscience Lab (ADN). Current work focuses on cognitive modeling of decision-making in both laboratory tasks and real-world settings, as well as machine
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line engineering, drug treatment studies) and flow cytometry is an advantage. Prior experience working with mouse models. Good computer skills and knowledge of Microsoft Word, Excel, GraphPad Prism, and
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, and cellular therapy. This research includes cell culture, transduction, transfection, retroviruses, lentiviruses, construction of vectors and DNA cloning, flow cytometry, cytolysis assays, cytokine
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collaboration among employees. Rutgers–Camden is recognized as a national model for civically engaged urban universities and was selected by the Carnegie Foundation for the Advancement of Teaching for a Community
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their goals and fosters collaboration among employees. Rutgers–Camden is recognized as a national model for civically engaged urban universities and was selected by the Carnegie Foundation for the Advancement
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. Certifications/Licenses Current CPR/AED and First Aid Certification, or ability to obtain it within the first six months of employment. A valid driver’s license would be required for this position. Current Rutgers
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Additional skills are a plus: ● Experience working with large and complex scientific datasets and data models ● Experience working with a DBMS in both on-cloud and on-premise environments ● Experience in C
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investigator and other laboratory members, including mammalian cell culture, protein extraction and electrophoresis, cell proliferation assays, flow cytometry, Western Blot, RNA and DNA isolation. Performs
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commitment to excellence. In return, RCRC offers accessible leadership, meaningful professional development, and the opportunity to help build a nationally recognized model for clinical research excellence
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, accountability, and a commitment to excellence. In return, (RC)2 offers accessible leadership, meaningful professional development, and the opportunity to help build a nationally recognized model for clinical