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with in vivo experiments (drug dosing, animal necropsy and surgery, animal infection), perform sample and data management (collect, analyze, and enter experimental data), maintain up to date laboratory
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received by 12/31/2028 12:00:00 AM. Discipline(s): Chemistry and Materials Sciences (12 ) Communications and Graphics Design (2 ) Computer, Information, and Data Sciences (17 ) Earth and Geosciences
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) Chemistry and Materials Sciences (12 ) Communications and Graphics Design (6 ) Computer, Information, and Data Sciences (16 ) Earth and Geosciences (21 ) Engineering (27 ) Environmental and Marine
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stochastic process. ARL Advisor: Jade L. Freeman ARL Advisor Email: jade.l.freeman2.civ@army.mil KEYWORDS: AI, Reinforcement Learning, Graphical Neural Network, Computational modeling, Optimization, Bayesian
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of electronic packaging and antenna structures. An objective of this project to establish process-material-design relationships for convergent manufacturing of conformal electronics embedded into Army munitions
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processing, nanotechnology, material science and technology, multifunctional technology, combustion processes, propulsion and flight physics, communication and networking, and computational and information
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modeling, digital/optical signal processing, nanotechnology, material science and technology, multifunctional technology, combustion processes, propulsion and flight physics, communication and networking
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development and implementation of EEG-based, passive brain-computer interfaces (BCIs) for optimization of human-machine teams, such as exoskeletons for physical augmentation in defense applications. The aim
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. Given data from such “in the wild” techniques, CCDC ARL researchers are seeking to apply machine learning methods to both predict behavior and make inferences about the underlying processes that generate
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modeling, digital/optical signal processing, nanotechnology, material science and technology, multifunctional technology, combustion processes, propulsion and flight physics, communication and networking