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Field
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of the art artificial intelligence/machine learning algorithms that are focused on human behavior modeling related to video classification using deep learning networks for end-users. Work with other team
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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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motivation to enhance our multidisciplinary research at the intersection of control theory and machine intelligence. Methodologies of interest include: Robot modelling, Nonlinear and Optimal control
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 12 days ago
comprehensive analysis simulations using CAMRAD II at Mars aerodynamic conditions Post-processing and analysis of DNS, CFD, or comprehensive analysis datasets Geometry creation and mesh generation for simulations
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than 1,800 employees and nearly 21,600 students. We are looking for a Postdoctoral Researcher in Robotics and Artificial Intelligence (RAI) (https://www.fieldrobotics.eu/ ) based at Department
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systems architecting AI/ML-driven clinical and operational decision support Digital health and learning health systems Healthcare operations, resource allocation, and workflow optimization Network, graph
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areas Biomedical applications, social determinants of health or other demographic health areas Spatial microsimulation, spatially weighted regression, combinatorial optimization or Bayesian network
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 12 days ago
entanglement on a robust, chip-scale architecture. 2. Background and Relevance to NASA This research directly supports NASA’s mission to develop disruptive technologies for the Integrated Network (IN) and
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, containerization (Docker), Kubernetes API development and web-based analytics tools Systems, Optimization, and AI ML/AI for mobility prediction and optimization Graph algorithms, network science Spatiotemporal
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ABIF can be found at: http://www.mcgill.ca/abif. Primary Responsibilities 1. Technical Development & Innovation Lead and document quality control (QC) workflows for ABIF imaging systems, including