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, analyzing the data on dynamics in individual behaviors. Successful applicants must have a PhD in computer science, digital technology, mathematics, or related fields with demonstrated experience in developing
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to develop novel enabling technology on hydrodynamic stability analysis that has applications in the study of the development of singularities, the long-time behavior of complex systems, the formation
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developing novel medical devices for ultimate human use. The successful applicant will join several fascinating projects on engineering novel approaches to improve the diagnosis and therapy of metabolic
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or more motivated post doctoral associates to work on cutting-edge research in the area of resilient concrete structures. Particular areas of interest include: UHPC mix development, material
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. The central goal of the laboratory is to study the neural mechanisms involving dynamic RNA modifications during cognitive development and decline. To achieve this, research projects rely on the use of a
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towards the development of robust coral populations resilient to climate induced stressors. Situated in a region with uniquely thermally tolerant corals, NYUAD offers a distinct setting for cutting-edge
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-quality and innovative research primarily focused on Control theory and ML methodologies for Field Robotics; Support the supervisor in developing and implementing the research agenda; Reproduce results
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that amplify human potential. The successful candidate will engage in innovative research projects in ML, focusing on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems
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Post-Doctoral Associate in the Center for Translational Medical Devices (Modeling) - Dr. Rafael Song
developing novel medical devices for ultimate human use. The successful applicant will join several fascinating projects on engineering novel approaches to improve the diagnosis and therapy of metabolic
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developing novel medical devices for ultimate human use. The successful applicant will join several fascinating projects on engineering novel approaches to improve the diagnosis and therapy of metabolic