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development of the group tasks and help in supervising PhD students. Applicants must have a PhD in experimental high energy physics or related field. Applicants need to submit a cover letter, curriculum vitae
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technologies and data sources; as well as the combination of traditional traffic flow theory concepts with new empirically derived models and data science ideas. Applicants must have received a PhD in
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consisting of PhD-level scientists, graduate students and undergraduate students, ensuring the candidate learns valuable skills in writing manuscripts and grant proposals, advising fellow researchers, and
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consisting of PhD-level scientists, graduate students and undergraduate students, ensuring the candidate learns valuable skills in writing manuscripts and grant proposals, advising fellow researchers, and
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initiating and designing their own research projects, leading the generation and analysis of experimental data, presenting project progress in meetings, training junior researchers and students, and publishing
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measurements for RIS enabled communication environments, as well as processing and analyzing the collected data. Applicants must hold a PhD degree in Electrical/Electronics Engineering, telecommunications
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learning, and Data-driven modeling and control. The Post-Doctoral associate will be based at NYU Abu Dhabi and will directly report to Prof. K.J.Kyriakopoulos in close collaboration with other researchers
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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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Physics, Spectral Theory, Quantum Chaos, Large Graphs and Quantum Walks. Related areas such as Quantum Information can also be considered. This position is offered through the research funds of Mostafa
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experimental data. Required Qualifications: A successful applicant must have a PhD in Engineering Mechanics, Civil Engineering, or Mechanical Engineering. Applicants are expected to demonstrate research