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competitive salary and benefits. Research in the SIT-D lab focuses on understanding and modelling consumers' behavior and decision process for sustainable transport modes and transport innovations. Research is
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models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations and/or experimental
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/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and
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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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of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or experimental means. The PDA is expected to actively disseminate results through publications in
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
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geotechnical applications Data acquisition and processing from monitoring systems Validation of modeling results against experimental and monitoring data Postdoctoral Associate Employment at NYUAD: The terms
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on natural language processing, computational linguistics, and data science. The main lab research areas are Arabic natural language processing (orthography normalization, grammatical error correction
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: Investigating membrane fouling mechanisms and mitigation strategies in desalination and water treatment processes. Developing and optimizing functional membranes, including electrically conductive membranes
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(UF), membrane distillation (MD), and nanofiltration (NF) processes. The role involves advanced membrane fabrication techniques and a range of membrane characterization methods, such as SEM, EDS, TGA