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Field
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development, the national security institute will advance national security in pursuit of a secure America. Within the Institute, multiple motivated applicants are sought to join as Research Faculty to support
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authentication modalities to develop more efficient and effective methods of generating biometric signatures of users. The newly developed modalities would rely on multiple user’s behavioral traits (e.g., typing
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and the project's co-principal investigators (from multiple organizations) to oversee a cross-organizational research team consisting of a group of postdoctoral associates, PhD students, and several
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applications, and AI integration with surgical robotics. The RA will design advanced algorithms and develop AI tools tailored for medical applications, bridging computational solutions with practical use
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and understanding human behavior from video. Specific research topics for human behavior using one or multiple cameras will focus on the design of efficient perceptual algorithms for behavioral cue
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analyzed. The tensor model structure estimated by suitable optimization algorithms, such as that recently developed in [GOU20], will be considered as a starting point. • Exploiting data multimodality and
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on advancing research at the interface of cognitive science and artificial intelligence. You will work with a diverse group of faculty, postdocs, and students from multiple disciplines, including cognitive
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, data structures and algorithms, through multiple languages, to build a foundation for advanced coursework in computing systems and theory, including graphics, database design, computer architecture
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the ability to support local people and communities everywhere. By working in and across multiple scientific areas, CALS can address challenges and opportunities of the greatest relevance, here in New York
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software and application-focused companies with interest in locating at IQMP and participating in the National Quantum Algorithm Center (NQAC). Identify industry needs and provide recommendations to internal