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to data and empower community-led, co-produced responses to public safety challenges. This position contributes to advancing an innovative, data-informed model of public safety that strengthens community
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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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methodologies are consistently applied and that financial information is accurately reflected across university schools, divisions, and administrative units. Develops and maintains allocation models, business
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experience supporting others. Certifications/Licenses Required Knowledge, Skills, and Abilities Knowledge about psychosocial rehabilitation and the recovery model is essential. Be able to work independently
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research requiring generation of mouse models of chronic asthma, measurement of airway resistance using Flexivent instrument with non-survival surgical procedures, legendplex assays, fluorescence activated
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is contingent upon continued funding availability. The successful position will lead an research program focused on elucidating the mechanisms that drive mitochondrial dysfunction in neurodegeneration
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ability to develop and lead a program of independent, NIH funded research. Candidates are expected to have an established federal grant portfolio that can be transferred to Rutgers. Successful applicant(s
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for supporting the data management, analysis, and visualization efforts within the Center’s Data Informatics Group (DIG) and for the NJ Climate Change Resource Center, which is also under the directorship
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both 2D and 3D models, for experimental studies. The ideal candidate will demonstrate a strong record of accomplishment in a relevant area of biomedical research, evidenced by first-author peer-reviewed
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applying relevant assessment and support skills with regard to a wide range of issues. Among the key duties of this position are the following: Models for clients’ good communication skills, recovery