57 phd-position-in-cryptography Postdoctoral positions at NEW YORK UNIVERSITY ABU DHABI
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machine learning. The successful applicant will participate in research involving human computation, knowledge discovery, machine learning, and data science. The position will provide the opportunity
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and tools. The lab website is http://www.camel-lab.com/ . Google Scholar of the lab is at http://scholar.camel-lab.com/ . The position will target the rank of Post-Doctoral Associate (within 3 years
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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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multidisciplinary team of researchers and graduate students. The postdoctoral associate will have access to state-of-the-art research facilities at NYUAD. This position supports two interconnected research streams
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learning theory to join the research team of Prof. Muhammad Umar B. Niazi. The position focuses on the design and implementation of incentive mechanisms for sociotechnical and cyber-physical-human systems
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life-cycle assessment. The post-doctoral associate will be expected to lead research efforts and contribute to publications in reputable academic journals. Qualifications: A PhD in Civil and
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life-cycle assessment. The post-doctoral associate will be expected to lead research efforts and contribute to publications in reputable academic journals. Qualifications: A PhD in Civil and
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the research team of Prof. M. Umar B. Niazi. The position focuses on the development of digital twins using physics-informed learning approaches, with specific applications to intelligent transportation
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, departmental seminars, and international conferences. Publish high-quality research articles in peer-reviewed journals. Engage in limited teaching and mentorship activities. Minimum Qualifications: PhD in
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have a PhD in Civil Engineering, Engineering Mechanics, or Mechanical Engineering. Applicants are expected to demonstrate research experience in the fields of structural modeling and machine-learning