28 algorithm-development-"Prof"-"Prof" Postdoctoral positions at NEW YORK UNIVERSITY ABU DHABI in United Arab Emirates
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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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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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computing where the focus will be to work on to the current efforts on accelerator developments towards the HL-LHC. Expertise in trigger development, performance and optimization and/or the ATLAS computing
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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
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Description The Water Research Center at New York University Abu Dhabi seeks to recruit a Post-Doctoral Associate to develop calix[n]arene-based covalent organic frameworks for water purification
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associate will lead collaborative efforts in advancing research focusing on the intersection of infrastructure, climate, and human health. Examples of current active projects include: Developing optimization
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. The project activities will involve the development of the theory and implementation of the advanced mechanics and numerical models as well as constitutive model calibration and validation based on physical
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that interface with human stem cells, investigate cellular and molecular mechanisms governing development and pathology, lead experiments from conception through publication in high-impact journals, mentor
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of the principal investigator, successful candidates will be encouraged to develop independent research projects as part of training for an independent research career. Candidates must hold a Ph.D. in Psychology
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aims to identify biomarkers in the eye and brain that explain vision loss, building on our previously-developed method linking clinical, neural and behavioral data (Allen et al., 2018; Miller et al