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System Model, vesion 3 (NorESM3), and a central satellite dataset for EEI is from the Clouds and the Earth’s Radiant Energy System (CERES). The specific tasks intended for the PhD fellow are to (i) Analyze
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automation frameworks, robotic process automation (RPA) tools, and machine learning/intelligence platform components; Knowledge of advanced data integration architectures, cloud-hybrid platforms, and API
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. In addition, he/she is expected to have advanced programming skills to troubleshoot problem scripts in various aspects of data analysis, including the Real Time data that is transferred to the cloud
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-on engineering. You will evaluate emerging storage technologies, lead deployment of petabyte-scale storage platforms, optimize performance, and develop secure, reliable storage services spanning campus, cloud, and
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, optimize, and scale our hybrid and public cloud infrastructure while writing and debugging application-level code. Your core focus will be driving efficiency within our AWS EKS and ArgoCD pipelines, while
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supports enterprise artificial intelligence platforms, cloud infrastructure, and integration services to ensure the reliable, secure, and compliant operation of AI technologies across the institution
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build collaborative relations with stakeholders. Preferred Qualifications Experience in higher ed. Five (5) years of experience with ERP payroll system software, such as Oracle HCM/Cloud and/or PeopleSoft
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recruitment strategies and enrollment into GED Boot Camps. Education Required: Bachelor's degree in Information Technology, Database Management, Cloud Computing, Computer Science, Computer Technology
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with Node, Typescript, AWS Cloud, including practical expertise across the following services: o AWS CDK Typescript o Lambda o API Gateway o SNS/SQS o ECS o DynamoDB o S3 o CloudWatch Proven experience
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routers and Ethernet switches. · Familiarity with virtualization (VMware, Hyper-V), cloud infrastructure (AWS, Azure), and security best practices. · Proficiency with monitoring tools, backup systems, and