61 model-driven-engineering-"Data-driven-Materials-Modeling" Postdoctoral positions at Rutgers University
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cancer. The role involves designing and executing complex experimental studies involving drug target evaluation, molecular pharmacology, cell culture models, and in vivo xenografts to evaluate targeted
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geophysical monitoring, data integration, and the development of predictive models and visualization tools. Candidates should have a PhD in geophysics, hydrology, environmental engineering, or a related
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will support and conduct simulation modeling research related to tobacco and lung cancer prevention and control. Duties include: Conducts data analysis using secondary data sources, such as national
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Position Details Position Information Recruitment/Posting Title Post Doc Associate Department Biomedical Engineering Salary Details $63,968 or other negotiated minimum salary Offer Information
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Sahoo and perform molecular/cellular studies of neuronal development using in vivo (mouse models) and in vitro (cultured primary neurons) models, involving skilled surgical procedures on mice and rats
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will support and conduct simulation modeling research related to tobacco and lung cancer prevention and control. Duties include: Conducts data analysis using secondary data sources, such as national
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, 41512056). This position will have the opportunity to gain strong training in cancer metabolism, cell growth signaling, and mouse models. The position is aiming at publishing high-profile papers and pursuing
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hematological neoplasms and aberrant cell signaling. Utilizing multi-omics, mouse models (GEMMs/PDXs), and human biospecimens, the incumbent will conduct independent research to uncover novel therapeutic targets
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sequence and to model the evolution of body size using bounded evolutionary models. 3) Biomechanical and Hydrodynamic Modeling: Apply computational fluid dynamics to test hydrodynamic hypotheses related
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. The postdoctoral associate will receive mentored training in environmental epidemiology, cancer survivorship, exposure assessment, survival analysis, mixture modeling, biomarker analysis, and health disparities