83 high-performance-computing Postdoctoral positions at Rutgers University in United States
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. Recently, Rutgers–Camden earned Carnegie classification as an R2 research university due to a high volume of internationally recognized research, creative output, and scholarly activity. Statement The School
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and Experience Ph.D. in Neuroscience, Genetics, Bioinformatics, Computer Science or a related science is required. Ph.D. Candidates who meet requirements with All But Degree (ABD) will be considered
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for cancer, including tumor-infiltrating lymphocytes and gene-engineered T cells. Postdoctoral Associates are expected to establish an innovative, collaborative research program addressing important and
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and analysis, including the development of new techniques and customized pipelines; (2) planet characterization combining space-based observations with ground-based, high-resolution spectroscopy; (3
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are required. Ability to publish scientific research papers/articles. The ability to work both independently and collaboratively is also essential. Must be computer literate with proficiency and working
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significantly. Devote 50% research time to arginylation research. Use 50% research time for independent interests and collaborations. Design, develop and perform enzymatic and cellular assays. Write papers and
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postdoctoral fellowship positions on our newly funded NIAAA Institutional Research Training T32 program, Training in Research on Alcohol use and its Consequences and Etiology (TRACE). The goal of this program is
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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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Qualifications Experience with health systems, healthcare policy, patient safety, and nursing informatics. Familiarity with federal and private funding mechanisms for nursing research. Equipment Utilized Physical
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collaborative and interdisciplinary research environment. Preferred Qualifications Experience with computational structural biology, molecular modeling, or AI-assisted drug discovery is desirable but not required