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Research Assistant / Research Associate (Software, AI & Autonomous Systems) Required Qualifications Bachelor's or Master's degree in Robotics, Computer Science, Artificial Intelligence, Electrical
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Research Fellow (Software, AI & Autonomous Systems) Required Qualifications PhD in Robotics, Computer Science, Artificial Intelligence, Electrical, Computer Engineering, or related disciplines. Key
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Call for applications for disciplines such as: electrical engineering, computer science, control systems, or related fields. In the "Navigation mobile Robots" research group, we develop autonomous
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inference) Algorithmic development for bilevel (or multilevel) optimization Methodological developments in Bayesian statistics and/or decision analysis Application of adversarial risk analysis within security
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11th October 2026 Languages English English English We are looking for a PhD student in Computational Neuroscience at the Kavli Institute for Systems Neuroscience PhD in Computational Neuroscience
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Center for Devices and Radiological Health (CDRH) | Southern Md Facility, Maryland | United States | about 20 hours ago
: The Artificial Intelligence Regulatory Science Program conducts regulatory science research ensuring safe and effective AI/ML-enabled medical devices across rapidly expanding healthcare applications including
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for one year and may be extended, subjected to performance and availability of research funding. Key Responsibilities: Develop state-of-the-art and innovative models and algorithms to improve port and
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 8 hours ago
-Computer Science Job Title Job Category Administrative & Managerial FLSA for Position Exempt Brief Summary of Work for this Position Research Execution & Algorithm Development Collaborate with PIs to execute
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algorithms for digital health and AI-driven research projects. Lead technical innovation by exploring and implementing emerging AI methodologies. Support data platform development and retrospective data
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a sequential decision-making process explored through computational simulation and deep multi-objective reinforcement learning. The project will investigate a simulation platform that reproduces