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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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. Contribute to the smooth operation of the laboratory. Participate in the academic activities of the division. This position does not include teaching duties and the SSEL provides financial support for travel
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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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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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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
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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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, the candidate will develop polymeric lubricious coatings for catheters to minimize injury to blood vessels during the trans-catheterization process. They will characterize the surface modifications of implants
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related techniques. Demonstrated ability to prepare, process, and analyze polymer samples. Familiarity with experimental design, data analysis, and maintaining laboratory instrumentation. Excellent
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candidate will be involved in cutting-edge research and development in 3D computer vision and machine learning for the digital preservation of cultural heritage. The project focuses on state-of-the-art