38 environment-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" Postdoctoral positions at The Ohio State University
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to work collaboratively in a team environment and contribute to a culture of innovation and excellence. Strong written communication skills. Desired: Self-motivated and able to work in a team with minimal
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biological datasets. Proficiency in R and/or Python and experience working in Unix/Linux computational environments. Familiarity with statistical methods for genomic data analysis, including differential
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Sciences | Clinical and Translational Science Institute The goal of this postdoctoral training program is to leverage the large, collaborative, and multidisciplinary research environment at Ohio State
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. Experience preparing manuscripts, presentations, and grant-related materials. Ability to work collaboratively in a multidisciplinary research environment. Location: Parker Food Science and Technology (0064
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bioinformatics tools in Linux-based or high-performance computing environments. The Postdoctoral Scholar will also perform microbial and viral community analyses, including diversity analyses, ordination
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Health | Division of Biostatistics The postdoctoral fellow will contribute to the HELM initiative at OSU, an interdisciplinary project that delves deep into the intersections of health, environment, and
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can execute efficiently, troubleshoot independently, and consistently deliver high-quality, publication-ready results. The postdoc will work in a fast-paced, collaborative environment, contribute
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positively to the department's research environment and mentor junior researchers within both the immediate research group and the broader astronomy department. Qualifications: Doctoral degree in Ph.D. in
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Project Office (TMPO). The successful candidate will also be expected to contribute positively to the department's research environment and mentor junior researchers within both the immediate research group
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biological data. · Proficiency in R and/or Python for data analysis and visualization. · Experience working with large datasets in an HPC or cloud computing environment. · Demonstrated ability to work