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, Python, R, or comparable platforms). Solid background in signal processing, statistics, time-series analysis, network science, or computational neuroscience. Excellent written, verbal and computer skills
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studies, including drug target evaluation, molecular pharmacology assays, cell culture models, and in vivo xenograft models to evaluate novel targeted therapeutic strategies. Data Analysis & Scientific
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. For additional information please see the Non-Discrimination Statement at the following web address: http://uhr.rutgers.edu/non-discrimination-statement
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. For additional information please see the Non-Discrimination Statement at the following web address: http://uhr.rutgers.edu/non-discrimination-statement
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. Actively participates and leads data analysis and the preparation of manuscripts, reports, and presentations. Assists the PI with the preparation of grant proposals. Assists with IRB submissions of ongoing
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calling and molecular data analysis. Preferred Qualifications Experience with advanced sequencing pipelines, variant calling workflows, or high-throughput assays (e.g., bulk/single-cell RNA-seq, ATAC-seq
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dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits/benefits-overview
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dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits/benefits-overview
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dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits/benefits-overview
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biomedical engineering or computer science, preferred. Demonstrated experience with electrophysiology data analysis, preferred. Strong quantitative and programming skills (e.g., MATLAB, Python, R) preferred