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(Docker, Kubernetes), and robust debugging techniques. Experience with cloud platforms (AWS, GCP, or Azure) and parallel computing, with a focus on cost-efficient and scalable model deployment. Skilled in
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Intelligence, Machine Learning, Data Science, Security and Privacy, Parallel and Distributed Computing, Deep Learning, Internet of Things (IoT), and Algorithms. Successful candidates will hold a
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resources to researchers at the University of Chicago. It is dedicated to enabling research by providing access to centrally managed High-Performance Computing (HPC), storage, and visualization resources
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(IEE) , the Chair of Highly-Parallel VLSI Systems and Neuro-Microelectronics offers a project position as Research Associate (m/f/x) Physics- and Quantum-Inspired Computing on the SpiNNaker2
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trusted enablers of technology for the U-M community. ITS works together to provide cohesive digital experiences and seamless support to the U-M community. Job Summary The Advanced Research Computing (ARC
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experience Strong practical knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing
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experience Strong practical knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing
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experience Strong practical knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing or
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experience Strong practical knowledge of machine learning with large datasets Experience : Experience with cloud-based, parallel, or distributed computing environments Hands-on experience developing or
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review processes and CI/CD pipelines Experience with collaboration and development platforms such as GitLab and CI/CD workflows Distributed storage systems and parallel file systems such as IBM Storage