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Posting Details Position Information Fiscal Year 2025-2026 Position Title Associate Director, Deep Tech Incubation Programs Classification Title Associate Director Department Business and
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conditions (Burgard et al., 2022). The application of deep learning to this problem has yielded promising results (Rosier et al., 2023; Burgard et al., 2023). Further development and refinement
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multisensor fusion and ondevice AI pipelines that guarantee tight latency, power efficiency, and fail-safe robustness. Driving hardware–software codesign to radically optimize state estimation and deep-learning
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will design and validate advanced multi-agent Deep Reinforcement Learning (DRL) and/or Digital Twin (DT)-enabled methods for efficient, scalable and time-critical handover optimisation. The work will
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basic 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
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to teach this undergraduate course at the Wee Kim Wee School of Communication and Information. The course examines narrative structures and strategies commonly used in different cinematic genres and to
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Deployment Strategies - Model Compression: Investigate techniques such as quantization, pruning, and knowledge distillation to reduce the computational and memory footprint of deep learning models without
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reconstruction - Estimation theory - computational methods and deep learning approaches. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR7249-HERRIG-026/Default.aspx Work Location(s) Number
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Description The Deep Learning laboratory in the Division of Science, New York University Abu Dhabi, seeks to recruit a research assistant to work on Deep Reinforcement Learning (DRL). The successful
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basic technologies, computer vision, image understanding, and other multi-media sensing and recognition techniques are widely studied. In addition, machine learning including deep neural networks