62 parallel-computing-numerical-methods-"Prof" Postdoctoral positions at NEW YORK UNIVERSITY ABU DHABI in United Arab Emirates
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of research interests, one letter of reference, and a transcript, all in PDF format. If you have any questions, please email Prof. Mohamad Eid at mohamad.eid@nyu.edu. The terms of employment are very
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Description The Division of Engineering at New York University Abu Dhabi seeks to recruit a motivated Post- Doctoral Associate to work under the supervision of Prof. Qurrat-Ul-Ain Nadeem
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research group of Prof. Monica Menendez. The group focuses on monitoring, modeling, and controlling the operations of multimodal transportation systems. Particular attention is paid to new vehicle
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will be under the supervision of CT&T Research Group Director Prof. Dr. Murat Uysal and is expected to carry out cutting-edge research on the physical layer design of wireless communication systems and
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
Geotechnical Engineering, Civil Engineering, or a related field, and should demonstrate strong expertise in at least two of the following areas: Large-deformation numerical modeling (e.g., Coupled Eulerian
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. If you have any questions, please email Prof. Fares Abu-Dakka at fa2656@nyu.edu The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be
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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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United Arab Emirates Application Deadline 1 Dec 2025 - 00:00 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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Experience in machine-learning modeling for solid mechanics applications Experience in the development and coupling of numerical methods for solid mechanics modeling Post-Doctoral Associate Employment at NYUAD
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aims to identify biomarkers in the eye and brain that explain vision loss, building on our previously-developed method linking clinical, neural and behavioral data (Allen et al., 2018; Miller et al