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. Of particular interest is the modeling of transport networks across multiple scales, including their function, development and remodeling. We employ advanced computational and theoretical techniques, such as
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provide insights into comparative physiology across different species. Of particular interest is the modeling of transport networks across multiple scales, including their function, development and
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in artificial intelligence (AI) for settings involving multiple interacting decision-makers---whether autonomous AI agents, humans, or a combination of both. Applications include mixed-autonomy
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from multiple disciplines and institutions. RESPONSIBILITIES: Write code and develop novel theoretical and practical state of the art artificial intelligence/machine learning algorithms that are focused
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use of data and algorithms. Excellent written and verbal communication skills and ability to communicate effectively with a variety of different stakeholders, e.g., academics, business executives
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. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and
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patients and cancer-free individuals, and will integrate these data alongside other data modalities (e.g., patient outcomes, functional genomics) to enable new clinically relevant discoveries across multiple
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multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and their dynamics. Conducting literature searches, manuscript preparation, and
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of approximately 1.7 million square feet and high-performance computing facilities at the DOD Supercomputing Research Center. This opportunity has multiple projects based out of the ERDC Field Research Facility in
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) at Harbor Branch Oceanographic Institute/Florida Atlantic University. Currently, SAIL is conducting multiple projects ranging from Hybrid Aerial Underwater Robotic System (HAUCS) – a cyber physical system