27 machine-learning-modeling-"https:"-"Computer-Vision-Center" positions in United Arab Emirates
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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, seeks to recruit a junior research scientist to develop AI-enabled healthcare applications. Key Responsibilities: Develop and fine-tune computer-vision models, instance segmentation, and retrieval-based
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for ethical AI. Integrate machine learning models, visualization dashboards, and backend services. Contribute to data collection, testing, documentation, and dissemination of open-source resources
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
, and real-time classroom monitoring. Design and implement machine learning models to analyze multimodal data (e.g., student behavior, engagement, and performance) to enhance personalized learning
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, machine-learning model development, structural sensing and health monitoring, conducting physical experiments, and validation of computational models. Required Qualifications: A successful applicant must
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IEEE Signal Processing Society’s journals and conferences. Strong background in communication theory, signal processing, machine learning, and optimization theory. Strong verbal and written skills in
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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in solid mechanics framework Experience in non-linear solid material response and fracture modeling Experience in machine-learning modeling for solid mechanics applications Experience in
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applications. Key Responsibilities: Develop and fine-tune computer-vision models, instance segmentation, and retrieval-based estimation from images and text metadata. Build and evaluate monocular depth pipelines
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
join forces to push the boundaries of data‑driven discovery. Our mission is two‑fold: to advance fundamental theory in probability and machine learning, and to translate those breakthroughs into high