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at scientific edge systems using large-scale HPC/AI computational and storage systems. Design and evaluation of ephemeral, user-configurable, and composable data and storage systems. Evaluation of cloud data
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biostatistics faculty collaborating with the Childhood Cancer Survivorship Program (CCSP). You will develop innovative biostatistical methods for childhood cancer survivorship research and collaborate with CCSP
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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
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of advanced statistical methodologies, and supporting research on high performance and cloud computing. The successful candidate will also be expected to offer 2-3 advanced technical or methodological workshops
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Fellow Campus Columbia Work County Richland College/Division College of Engineering and Computing Department CEC Electrical Engineering Anticipated Hiring Range $52,526 - to commensurate with
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computing and/or cloud computing; familiarity with Earth system models through model development, model execution, and/or model performance diagnoses; applied mathematics methods such as machine learning
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interactions, or aerosol–cloud interactions Strong experience in numerical modeling and high-performance computing • Experience applying AI/ML methods to model development, with strong programming skills (e.g
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research prototypes to real-world deployment environments, including cloud, secure enclaves, trusted research environments, and leadership computing platforms. Candidates should be comfortable working in a
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in internal meetings and at national/international conferences. ● Collaborate with an interdisciplinary team (bio)statisticians, data scientists, computer scientists, and climate scientists
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with PyTorch, required to have experience developing code with a team through collaborative version control Experience working with large datasets and cloud computing environments. Solid background in