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Field
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analysis, computer vision, or machine learning, with a clear interest in developing image analysis algorithms and an affinity with medical topics. Good communication and organizational skills are essential
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and human-based leadership. As organizations increasingly blend algorithmic and human decision-making, fundamental questions arise about how leadership operates, adapts, and creates value in this new
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. This longitudinal project investigates the implementation of AI-empowered chronic disease management systems in hospitals. It examines human-AI collaboration and the "boundaries of work" between humans and algorithms
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help develop new computational models that integrate molecular reaction networks with AI/ML algorithms in order to predict patient-specific cardiac remodeling and heart disease outcomes across human
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constraints. The postdoc will work at the interface of reinforcement learning and computational epidemiology, focusing on the development of new reinforcement learning algorithms. The project will consider
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with Prof. Mauro Maggioni on problems that include: analysis and algorithms on graphs, geometric analysis of high dimensional data sets, dynamic data sets, scientific machine learning, high-dimensional
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cleaning, filtering, etc.).•Expertise in data fusion and relevant algorithms (deep learning, generative AI, kernel methods, Bayesian methods). •Preferably, experience with high-content imaging or cell
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expected to actively contribute to the project, work collaboratively as part of the research team, and perform the following major tasks: Conduct theoretical analysis, algorithm development, and simulation
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-seq, single-cell RNA-seq, and spatial data) and experience in multi-omics data integration. Has the ability to develop algorithms and code for innovative multi-omics data analysis. Baylor College
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? How do social media algorithms influence what information the public encounter? How does AI reshape who and what audiences trust when forming opinions? You are expected to leverage on mixed-method and