116 structural-engineering-"https:"-"https:"-"https:"-"https:"-"https:"-"NOVA.id" positions at NEW YORK UNIVERSITY ABU DHABI
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completing a bachelor’s or master’s degree from a recognized institution Bachelor’s/ Master’s degree in computer science, mathematics, computer engineering, or relevant technical field Demonstrable research
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Description The Laboratory for Computer-Human Intelligence (CHI-lab, https://www.x-labs.xyz ) in the Division of Engineering, New York University Abu Dhabi, is seeking a highly motivated
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
) for Smart Infrastructure Management Systems to work under the supervision of Professor Borja García de Soto, director of the S.M.A.R.T. Construction Research Group and Co-PI in the SHORES Center
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structure determination using electron or X-ray crystallography. Candidates must have substantial experience in crystallography, specifically in the structure solution and refinement of small molecule
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the areas of Artificial Intelligence (AI) for materials science, with an emphasis on structure-property-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates
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possibility to investigate cutting-edge interdisciplinary questions within the theoretical and fundamental aspects of Computer Science and Engineering, Mathematics, and Physics, from various points of view and
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already hosts Le Louvre Abu Dhabi, and several other museums are in construction. The position includes funds for the implementation of the artist’s project, a competitive salary, a housing allowance, and
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of responsive covalent organic frameworks (COFs) for diverse challenges in water treatment, health, and energy. This role will emphasize the directed synthesis and structural design of COFs tailored to achieve
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
Description The Research Center SHORES seeks to recruit a Postdoctoral Associate to work in the field of geotechnical engineering. Required Qualifications: The ideal candidate will hold a PhD in
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, Electrical Engineering, Artificial Intelligence, or a related discipline. Strong interest in 3D computer vision and machine learning methods. Proficiency in Python and experience with deep learning frameworks