32 algorithm-development-"Prof"-"Washington-University-in-St"-"Prof" Postdoctoral positions at NEW YORK UNIVERSITY ABU DHABI
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on adaptive evolution in invasive species, using the mesquite tree (Prosopis sp.) as a model system. This position will be based at NYU Abu Dhabi and supervised by NYUAD-CGSB’s Director, Dr. Stephane Boissinot
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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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Description The Water Research Center at New York University Abu Dhabi seeks to recruit a postdoctoral associate to work on the development of responsive membranes with in situ switchable properties
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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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candidate will work under the supervision of Professor Raed Hashaikeh in the Mechanical Engineering department. This project focuses on the development and optimization of conductive membranes
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, climate, and human health. Examples of current active projects include: Developing optimization models to analyze and mitigate fine particulate matter (PM2.5) exposure from various infrastructure systems
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, climate, and human health. Examples of current active projects include: Developing optimization models to analyze and mitigate fine particulate matter (PM2.5) exposure from various infrastructure systems
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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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the connections between accretion and ejection. The processes involved in triggering outbursts, using optical monitoring and the real-time pipeline X-ray Binary New Early Warning System (XB-NEWS) developed at NYUAD
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Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a