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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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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 17 hours ago
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
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particular sequential, multiple assignment, and randomized trial design. You will have the opportunity to mentor the PhD students on the team. Experience in any of the following areas may be useful: SMART