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methodologies in brain diseases. The candidate will work on developing advanced new algorithms, testing and validation, and applications in these data modalities. The candidate will have the opportunity to work
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algorithms aimed at predicting pathogen potential based on whole or partial genomes. You will also be responsible for integrating such tools into online accessible pipelines thus, providing the possibility
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scalability and resource efficiency through the development of cooperative, distributed AI algorithms, optimising data, energy, and processing resources while adapting to the different computational
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. The investigator collaborates with interdisciplinary clinical teams to integrate these computational tools directly into hospital workflows. Routine duties include algorithm optimization and the evaluation of model
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verticals, Unmanned Aerial Vehicles, Integrated Satellite-Space-Terrestrial Networks, Quantum Communications and Key Distribution, Spectrum Management and Coexistence, Tactile Internet, Earth Observation, and
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 3 months ago
distribution on a global scale. This project will focus on developing a strategy to best utilize this data in a global atmospheric data assimilation framework. Activities that would be involved in this project
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Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis algorithms for critical equipment (e.g
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, and evaluation in distributed and privacy-aware settings. While the position is supported by an AI for Science project on privacy-preserving federated learning, the broader objective is to advance
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application! Work assignments This position focuses on the development of theoretically grounded and practically scalable decentralized learning algorithms under realistic system constraints, including
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and resilience across heterogeneous computational resources while addressing workflow requirements for scientific applications. Validate distributed intelligence algorithms at scale on ORNL's