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, high-impact, and original research. Research topics include, but are not limited to; machine learning for large models, trustworthy AI, explainable AI, deep learning, reinforcement learning, optimization
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multidisciplinary teams, overseeing financial operations, and optimizing program delivery in a multicultural, international setting. Preferred Experience: Experience working in a higher education environment in
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many-years of R&D experience in cross-layer design and optimization for building energy-efficient and robust AI/ML and vision systems, including efficient learning and inference of complex AI/ML
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, dynamical systems, optimal transport, spectral theory, singularity formation, scattering, long time dynamics. Exceptional candidates in all fields of mathematics will be considered. NYUAD is strongly
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apply. A PhD dissertation or research papers that demonstrate a strong interest and research focus in any of risk analysis or minimization, robust optimization, deep learning for systems, probabilistic