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Field
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Education: PhD in Chemical Engineering or related field Desired Experience: 3 years of prior research experience on multiscale modeling, hybrid modeling, and model-based control or related fields. Additional
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Education: PhD in Chemical Engineering or related field Desired Experience: 3 years of prior research experience on multiscale modeling, hybrid modeling, and model-based control or related fields. Additional
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on understanding the pathogenesis of idiopathic Pulmonary Fibrosis (IPF), and aging as a major risk factor for IPF. Our studies are aimed to mapping senescence cells and identify novel therapeutic targets to control
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including: CRISPR-based genetic screening High-throughput microscopy Confocal microscopy Flow cytometry and cell sorting Functional genomic profiling Contribute to in vivo studies using mouse models and
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, addiction medicine, psychiatry, and/or HIV. Experience with longitudinal and repeated measures analysis, difference-in-differences designs, or group-based trajectory modeling. Experience with negative control
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-dimensional documentation and recording of archaeological materials and structures using high-precision 3D scanners and in processing digital models. • Track record of scientific publications in prehistoric
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to offering competitive and flexible compensation packages to attract and retain top talent. Benefits Rutgers offers a comprehensive benefits package to eligible employees, based on position, which includes
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specifically in neurons exhibit a spectrum of behavioral abnormalities characteristic of mouse models of psychiatric disorders. The primary scope of the current project is to dissect the functions of AMOTL1 in
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separations in controlled environments such as radiological hoods, gloveboxes, and hot cells Design, assemble, operate, troubleshoot, test, and optimize experimental systems and specialized apparatus, including
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. This position is designed for scientists with strong computational and quantitative training who are interested in agent-based modeling, network science, infectious disease dynamics, uncertainty quantification