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of complex and challenging patients in critical care. The curriculum is composed of multi-modal learning opportunities that may include the following: in-person didactics, online classrooms, simulation
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, Algorithm, Extremal Graph Theory, Computing Theory o Programming Language, AI Theory or Machine Learning o Classical and Quantum Algorithm for Computational Quantum Many-body Theory o Theory and Computation
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on leveraging data from permanent forest plot datasets in the Caribbean to build a comprehensive view of tropical tree species in support of conservation and broader management actions. Learning Objectives
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to work within a team environment. Adaptability to a fast-paced, dynamic environment. Multitasking essential. To learn more and apply, please visit: https://careers.dana-farber.org
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. Have relevant research/industry experience in Machine Learning, AI and Privacy. An excellent team player who can cope with an agile and fast-paced environment. Good communication and interpersonal skills
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platform that utilizes deep learning to analyze images of bruises. Responsibilities: Responsible for developing components of the project platform or deep learning application; Supervises a team of graduate
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software testing and Machine Learning components. This research will have real-world impact through close collaboration with industry partner and offers the opportunity to contribute to cutting-edge
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research, oncology microbiomes, or environmental resistome surveillance. Familiarity with spatial metagenomics, single-cell microbiome analysis, or multi-omics data integration. Knowledge of machine learning
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interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and functional neuroimaging data. Specific activities may include
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from sensors or other continuous data sources. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages