123 parallel-computing-numerical-methods-"Simons-Foundation" positions at NEW YORK UNIVERSITY ABU DHABI
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perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems This position
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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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infrastructure monitoring, as well as connected autonomous vehicles Integrating multi-modal sensor data with physics-based models Developing robust and adaptive methods for real-time parameter and state estimation
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will support cutting-edge projects in urban science, computational social science, and usability research. You’ll work closely with our team of Principal Investigators (PIs) to design and implement data
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methods (e.g., EIS, CV) and surface functionalization. Knowledge of materials for charge transport and ion exchange. Prior collaboration with international or multidisciplinary research teams. This position
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, including behavioral and neuroimaging (EEG/MEG and/or MRI) data. These studies will be informed by computational modeling and will use cutting-edge data analysis methods. The project will build on recent work
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2 Sep 2025 Job Information Organisation/Company NEW YORK UNIVERSITY ABU DHABI Research Field Computer science Physics Researcher Profile Recognised Researcher (R2) Established Researcher (R3
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), and cyclic voltammetry to assess membrane properties. Contribute to the development of scalable fabrication methods and explore potential industrial applications. Present findings in lab meetings
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2 Sep 2025 Job Information Organisation/Company NEW YORK UNIVERSITY ABU DHABI Research Field Computer science Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Country United
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robust brain-inspired, autonomous, and cognitive systems through cross-layer analysis and design methods, engaging hardware, software, and system level techniques synergistically. Prof. Shafique’s lab has