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to develop applied research skills in machine learning, interact with an international network of collaborators, and gain post-doctoral research experience. The ideal candidate is self-motivated and can work
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inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic
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, with particular emphasis on smart mobility and urban transportation networks. In particular, the successful candidate will conduct cutting-edge research in: Adaptive incentive mechanism design for
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(e.g., transportation networks, manufacturing systems, and truck routing). Assessing the relevance of the intake fraction (i.e., exposure efficiency) of major emission sources as a critical metric for
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separation processes. Strong attention to detail, excellent organizational skills, and exceptional verbal and written communication abilities are essential. The candidate should be capable of working both
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Engineering, or any closely-related field. Excellent communication skills in English, the ability to work in multi-disciplinary teams, and scientific creativity are essential. NYUAD offers a stimulating
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systems (ITS). In particular, the successful candidate will conduct cutting-edge research in: Developing physics-informed neural networks (PINNs) for complex dynamical systems modeling and observer design
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(e.g., transportation networks, manufacturing systems, and truck routing). Assessing the relevance of the intake fraction (i.e., exposure efficiency) of major emission sources as a critical metric for
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learning Foundation models, including large language models Agentic AI Multi-agent AI systems Transfer learning Self-supervised learning Federated learning The Postdoctoral Researcher will be primarily based
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Description The New York University Abu Dhabi Computational Approaches to Modeling Language (CAMeL) Lab seeks to hire a post-doctoral researcher to work in any of the lab research areas, to be