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for supply chain and marketing optimization. The project will integrate machine learning, deep learning, foundation models, and interpretable AI approaches, ensuring scalability, robustness, and industrial
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experimental design. Hands-on experience with classical machine learning methods such as linear/logistic regression, decision trees, and gradient boosting. Familiarity with deep learning concepts and modern
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the competent authority of the Ministry of Higher Education, Research and Innovation (MESR). "Video content security in a deep learning coding architecture" Over the past few decades, numerous video compression
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of academic programs within the UCLA Joe C. Wen School of Nursing. This position requires deep familiarity with the School's unique curriculum, policies, systems (including Bruin Learn), and existing
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@emploi.beetween.com Requirements Research FieldComputer scienceEducation LevelPhD or equivalent Skills/Qualifications Expected skills: Hold a Ph.D. in Deep Learning, Statistics, or a related field. Solid experience in
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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evolutionary datasets across time scales Project Context The NSF-funded project 'Unlocking New Horizons - How Feeding Morphology and Performance Impacts Adaptive Expansion in Deep Time', seeks to examine how
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challenging and impactful research and development programs in healthcare informatics, bioinformatics, high performance computing and deep learning. We have a collaborative environment focusing on designing
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to contribute to the development of innovative machine learning solutions using deep learning and multimodal foundation models. Working closely with leading researchers, you will design, develop, and implement
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environment. Key research Objectives: AI Innovation (Taxonomic Identification): Developing and optimizing deep-learning architectures (e.g., YOLO) for the automated detection and classification of nocturnal