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Field
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partnership with CentraCare, the regional campus in St. Cloud offers a wide range of patient experiences throughout students’ education in Greater Minnesota and prepares them to become exceptional clinicians
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with cloud-based computing platforms (AWS, Azure, Google Cloud) and high-performance computing (HPC) environments. Understanding of data privacy, security, and ethical considerations in handling clinical
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detection. Familiarity with real-time applications of AI/ML in embedded or IoT devices. Knowledge of cloud-based computing platforms for data processing (e.g., AWS, Google Cloud). Understanding of BMS
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functions, predictive models or quantum chemistry Machine learning or AI frameworks applied to molecular discovery. Familiarity with cloud or high-performance computing environments. Experience collaborating
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PhD degree is required. Develop protocols for real-time phenotyping of NUE-related traits using the TraitFinder phenotyping system. Build and validate digital twin models using 3D point cloud and
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in modelling the systems as large clouds of interacting particles and to derive and analyse reduced models in the infinite particle limit. Often, the interaction between the particles can be modeled
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application teams and contribute to broader initiatives, including the American Science Cloud (AmSC) AI Services efforts, and to help us with design of future systems and data-management solutions to meet needs
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security, and reproducible experiments. Strong programming skills (e.g., Python/C++); ability to prototype and evaluate security controls on cloud-native stacks (Docker, Kubernetes, Helm). Records
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Biology provides access to high-performance computing clusters, a cloud computing environment, innovative visualization tools, highly automated analytical pipelines, and mentorship from faculty scientists
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). Knowledge of high-performance computing or cloud environments for large-scale data. Strong collaboration skills and ability to work in interdisciplinary teams. Special Requirements: Applicants cannot have