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Intensive in Microbial Bioinformatics, providing instruction and mentorship in R, Python, and command-line tools for microbiome and metagenomic analysis. Collaborate with faculty, staff, and industry partners
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Intensive in Microbial Bioinformatics, providing instruction and mentorship in R, Python, and command-line tools for microbiome and metagenomic analysis. Collaborate with faculty, staff, and industry partners
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requirements to technical specifications and coded data pipelines. Work with tools, languages, data processing frameworks, and databases such as R, Python, SQL, MongoDB, Redis, Hadoop, Spark, Hive, Scala
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, including classification, regression, clustering, and deep learning algorithms. • Statistical Software: Proficiency in statistical software such as SAS, Stata, R or Python, including relevant packages
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the JAX Python library, including efficient implementations of classical numerical algorithms. 2. Extend the hybrid FEA-ML framework to include nonlinear cohesive zone models with simple traction separation
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by research computing Proficiency in scripting or programming (Python, Go) for custom automation. Type Benefited Staff Special Instructions Summary Additional Information The University of Utah values
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by research computing Proficiency in scripting or programming (Python, Go) for custom automation. Type Benefited Staff Special Instructions Summary Additional Information The University of Utah values
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Target Characteristics: Broad grasp of modern science techniques and approaches deriving. Strong understanding of SQL, light understanding of R or Python helpful. Analytical, creative, perceptive
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qualitative data. Proficiency in data management and visualization tools (e.g., Excel, Power BI, R, or Python). Type Benefited Staff Special Instructions Summary Additional Information The University of Utah
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the position description. Preferences The ideal candidate will have experience with wearable sensors and/or remote monitoring approaches and strong programming (e.g., R, Python, or similar) and writing skills