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cyber-physical systems, with a particular focus on Internet-of-Things (IoT) and the computing continuum era. Our vision is to pioneer advancements in high-tech distributed and embedded systems
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principles and research data management. Experience with high-performance computing, cloud computing, GPU acceleration, or distributed data processing. Experience participating in international scientific
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-year Postdoctoral position focused on modeling the flexibility potential of electric vehicle (EV) charging clusters and exploring their synergies with distributed renewable energy sources
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and parallel computing, or scientific simulation; Effective oral and written communication skills; Ability to work well independently as well as in a collaborative team environment. COMPENSATION AND
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, contrastive learning, or representation learning approaches Experience with high-performance computing, cloud platforms, or distributed training Prior experience working in a collaborative biomedical
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federated learning SOTA algorithms. Knowledge of distributed optimization and consensus algorithms. Knowledge of large models and hyper-parameter optimization. Knowledge of high-performance computing and its
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Your privacy, your choice We use essential cookies to make sure the site can function. We also use optional cookies for advertising, personalisation of content, usage analysis, and social media, as
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career taken into consideration. Additionally, your resume must comprise: A PhD or equivalent Research experience in Software Engineering, Distributed Software Systems, Edge and Cloud Computing A
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). We are looking for a person with: A PhD in computer science or a related field, with a software systems profile: distributed systems, cloud or edge computing, simulation, digital twins, model-based
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The University of Texas MD Anderson Cancer Center | Houston, Texas | United States | about 10 hours ago
computational biology, physics and (bio)statistics, biology or medicine. Applicants must have a proven publication record. Prior experience with handling massively parallel sequencing data is considered an