61 postdoc-in-thermal-network-of-the-physical-building Postdoctoral positions in United Arab Emirates
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monitoring, conducting physical experiments, and validation of computational models. Required Qualifications: A successful applicant must have a PhD in Civil Engineering, Engineering Mechanics, or Mechanical
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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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applicant will manage projects, build deep technical knowledge and develop transferable solutions. He/she will participate in developing novel concepts and writing proposals. He/she will work towards solving
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, mathematics, and innovation. Candidates must hold (or be close to completing) a Ph.D. in Applied Mathematics, Electrical or Mechanical Engineering, Physics and Applied Physics or a related field. Working in a
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will be under the supervision of CT&T Research Group Director Prof. Dr. Murat Uysal and is expected to carry out cutting-edge research on the physical layer design of wireless communication systems and
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Description The Advanced Materials and Building Efficiency Research Laboratory (AMBER Lab) in the Division of Engineering, New York University Abu Dhabi, seeks to recruit a post-doctoral associate
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, and NYU Shanghai, form the backbone of NYU’s global network university, an interconnected network of portal campuses and academic centers across six continents that enable seamless international
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of NYU’s global network university, an interconnected network of portal campuses and academic centers across six continents that enable seamless international mobility of students and faculty in
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undergraduate program in the Arts, Sciences, Social Sciences, Humanities, and Engineering. NYU Abu Dhabi, NYU New York, and NYU Shanghai, form the backbone of NYU’s global network university, an interconnected
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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., 2019; Pedersini et al., 2023). We