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working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI systems
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, telecommunications or related field. Other requirements include Strong background in communication theory, signal processing, and wireless communications, Extensive experience in physical (PHY) layer algorithm design
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. RISC invites qualified applicants in the areas of electrical, computer, or mechanical engineering, or other related department to apply. The successful applicants will design controllers for a variety of
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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multimodal interaction are encouraged to apply. Applicants must have received a Ph.D. in electrical engineering, computer engineering, computer science or a related field by the time they join, and at least
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on representing the structural response Physical experimental testing for structural and geotechnical applications Data acquisition and processing from monitoring systems Validation of modeling results against
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Description NYUAD Water Research Center at New York University Abu Dhabi, seeks to recruit a research scientist to work on the development of membrane desalination to treat water from the Arabian
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systems capable of understanding, learning, and acting in complex, dynamic settings. The team works at the intersection of computer vision, multimodal learning, and robotics to create next-generation
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Junior Research Scientist in the Center for Quantum and Topological Systems (CQTS) – Dr. Hisham Sati
arises. Applicants must have a Bachelors in one of the following: Computer Science, Computer/Electrical/Communication Engineering, Mathematics, Physics. For consideration, applicants need to submit a cover
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natural language processing and machine learning workflows; (3) experimental design and causal inference (including virtual lab experiments); and/or (4) network or computational modeling. The ideal