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Information Theory. While excellent candidates with other research interests might be considered, priority will be given to those able to relate to one or more of the above topics. Applicants must have a PhD in
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environment alongside PhD-level engineers and scientists, graduate students, and full-time researchers. They will also have the chance to contribute to other projects within CENTMED, working on cutting-edge
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at NYU Abu Dhabi. The researcher will report directly to Dr. Farah Shamout and work in close collaboration with other researchers, PhD students, and undergraduate research assistants. The researcher will
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independently, has a passion for AI and its applications, and is willing to learn new technologies. The candidate should have a PhD in Computer Science or a closely related field. Relevant background and skills
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multidisciplinary environment consisting of PhD-level scientists, graduate students and undergraduate students. Applicants must have a BS (MS preferred) in an engineering or biomedical-related discipline, two years
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electrophysiological methods like MEG. The candidate will work in a multidisciplinary environment consisting of PhD- and MA-level scientists, and undergraduate students. Applicants must have a BA in Psychology or
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independently and collaboratively within a team. Applicants must have a PhD in materials science and engineering, chemical engineering, or related field. Excellent experimental and analytical skills relevant
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of PhD), or Research Associate (more than 3 years of PhD). A strong preference is for individuals with (a) computer science or computer engineering degrees with previous experience in natural
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. Contribute to mentorship of students and lab group discussions. Minimum Qualifications: PhD in Chemical Engineering, Environmental Engineering, Materials Science, Mechanical Engineering, or a related field
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. Successful applicants must have a PhD in a field related to survey methods techniques and transport demand modelling and demonstrated experience with state choice experiments, discrete choice models, virtual