136 high-performance-computing research jobs at Rutgers University in Ireland-University-Ranking-2024
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methods. In addition, systematic phenotyping of the strains in the collection such as measurement of their relative growth rates, will be performed to add more value to this collection for the community
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programs, and a licensed therapeutic school from preschool through high school. Specialty services include the New Jersey suicide prevention helpline and peer help lines for police, veterans, active military
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Posting Number 26FA0840 Posting Open Date 10/02/2026 Posting Close Date 10/30/2026 Qualifications Minimum Education and Experience PhD in Ecology, Geography, Environmental Science, Biology, Computer
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perturbations, including changes in gene expression, enzyme activities, cellular phenotypes, and metabolite production; and 3) performing statistical analyses of human clinical and/or omics data to evaluate human
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University of New Jersey is seeking a Post Doc Associate for the Brain Health Institute within Rutgers Biomedical and Health Sciences (RBHS). The primary purpose for the Post Doc Associate is to perform
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for coupling functional genomics techniques with computational analyses to understand gene regulation in health and disease. Such models are based on multi-omics high-throughput assays, either performed by
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in quantitative methods. Must have high proficiency in R and/or other computer programming languages. Applicants in All But Degree Status will be considered for interviews. Preferred Qualifications
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in special areas of interest to the overall research program of the laboratory. Performs highly skilled on experiments and data analysis to dissect transcriptomic, metabolomic, proteomic changes in rat
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Mycobacterium tuberculosis and Mycobacterium abscessus by comparing the transcriptomes and proteomes in cells with or without toxin expression. Perform any relevant assays to validate these results. Study the
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-scale energy models to analyze high-performance buildings and geothermal energy systems. (3) Assess technical and non-technical barriers to the adoption of clean energy technologies. (4) Conduct analyses