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control algorithms (such as adaptive control or model predictive control) to reliably maneuver Army projectiles to the target despite limited state information, control authority, and changing flight
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biological development, reproduction, sex determination, and/or olfaction/chemical sensing in tephritid pests of agriculture. The research opportunity will allow the postdoc to develop and/or improve
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? Under the guidance of a mentor and as the selected candidate, you will learn how to apply algorithms to predict parts of coding and noncoding sequences for optimization. As a result, designed mRNA
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) to introduce, preserve, evaluate, regenerate, distribute tropical fruit germplasm and develop cultural and management systems for tropical/subtropical crops that are of economic importance to the Continental and
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control systems and thermal protection for on-board actuation systems. The candidate will have a deep knowledge of smart material based actuators, mechanisms, advanced control algorithms, and thermal
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potency of new threats, and microphysiological systems (organs-on-chips) for functional characterization of organ toxicity and in vitro ADME (absorption, distribution, metabolism and excretion) assays
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sampling of information in decision-making Decision-making algorithms for human-robot collaborative tasks Game theory applied for multi-agent learning Distributed optimization communication for collaborative
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hardware implementing Deep Reinforcement Learning algorithms for the tactical arena. Additionally, High Level Synthesis (HLS) will be incorporated to obtain hardware designs optimized for various criteria
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framework, including host and vector distributions, confirmed georeferenced reports of VS cases in the United States and Mexico, and publicly available environmental layers derived from satellites
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collection of streaming sensor data. This project focuses on utilizing state-of-the-art reinforcement algorithms to 1) dynamically learn from multi-agent actions and context, 2) evaluate the environment and