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Field
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learning algorithms for early damage detection, health indicator extraction, and remaining useful life prediction. The successful candidate will take a leadership role in experimental integration and data
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data management sufficient to create, transform and integrate data in a variety of resolutions and formats. Analysis will include running machine learning algorithms (e.g., Random Forest, CART) and
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work with Dr. Anna Dawid and her research team. The position is set in the exciting, friendly, and interdisciplinary environment of the aQa (Applied Quantum Algorithms) group, which is a team of faculty
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. The work includes theoretical analysis, algorithm design, and validation on realistic case studies, as well as dissemination of results through publications, open-source code, and collaboration with internal
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algorithms, ideally in the healthcare or mental health domain Desirable criteria Track record of successful research grant applications, or attempts to obtain grant funding. Previous development of ML-based
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model algorithms for livestock enteric fermentation and manure housing and management using a scientific programming language. Integrate the modules into the APEX ecosystem simulation model. Assess and
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for transmission or distribution grids, synchronous generators, large loads, transmission networks, etc. Develop simulation algorithms that enable large-scale simulations. Integrate (or co-simulate) grid component
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complex sociotechnical systems Strategic learning and equilibrium-seeking algorithms in transportation networks Game-theoretic approaches to cybersecurity and security games Integration of human behavior
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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conditions, identification of vulnerabilities, and development of resilience enhancement strategies. Contribute to the design, development, and implementation of new models, methods, and algorithms