37 parallel-and-distributed-computing-"UNIS"-"Meta"-"Humboldt-Stiftung-Foundation" positions in United States
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, debugging), including CI/CD, containerization (Docker, Kubernetes), and robust debugging techniques. Experience with cloud platforms (AWS, GCP, or Azure) and parallel computing, with a focus on cost-efficient
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exploring them. Basic data preprocessing, feature engineering, and model evaluation, or a strong willingness to gain hands-on experience. Eagerness to learn HPC concepts, including parallel computing
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to begin September 1, 2025. We will consider strong candidates in any research area but will prioritize Distributed and Parallel Computing. A PhD in computer science or a related area is required
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services, distributed web authentication, LDAP, computing account management, and other similar technologies, as well as auditing software, centralized antivirus management, intrusion detection systems
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services, distributed web authentication, LDAP, computing account management, and other similar technologies, as well as auditing software, centralized antivirus management, intrusion detection systems
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with the architecture and performance characteristics of distributed computing and data handling systems. Extensive knowledge in computer science or related field, demonstrated through education or
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based on MPI. Experience working with the architecture and performance characteristics of distributed computing and data handling systems. Extensive knowledge in computer science or related field
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learning, AI engineering, AI infrastructure, hybrid cloud computing, and parallel programming with GPUs, to work at the Institute for Artificial Intelligence and Data Science (IAD). As a Senior Research
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data analysis and visualization. The faculty member’s research program is expected to develop and incorporate novel algorithms and frameworks, such as deep learning, parallel and distributed computing
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, hybrid cloud computing, and parallel programming with GPUs. As a Junior Research Engineer, you should have some basic understanding and experience in the development of scalable AI systems and deployment