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of existing and emerging networks and communication systems, with a possible starting date in January 2025 (or later). The group’s research builds upon the areas of system, network, information, and computer
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the frontiers of developmental biology and disease modeling. The laboratory integrates stem-cell biology, fluorescence imaging, bioinformatics, and advanced nano- and micro-engineering to decode organogenesis and
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, Neuroscience, or a related field. A strong background in functional neuroimaging with experience in decoding and/or encoding models is required. Candidates with experience with recurrent neural networks will be
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129188, United Arab Emirates [map ] Subject Areas: Probabiltiy, Computer science, artificial intelligence Appl Deadline: 2025/09/30 11:59PM (posted 2025/07/29, listed until 2026/01/29) Position
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, climate, and human health. Examples of current active projects include: Developing optimization models to analyze and mitigate fine particulate matter (PM2.5) exposure from various infrastructure systems
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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 can be filled
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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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, climate, and human health. Examples of current active projects include: Developing optimization models to analyze and mitigate fine particulate matter (PM2.5) exposure from various infrastructure systems
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Description The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in
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experience in the fields of computational mechanics and computational geomechanics. Preferred Qualifications: Experience in the following areas is preferred: Experience in modeling geomechanical systems