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Field
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healthcare application needs to analyze sensitive patient data across distributed nodes. Researchers and students can explore privacy-preserving algorithms and technologies like federated learning and zero
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to develop and implement pulse sequences and reconstruction algorithms on Siemens and GE platforms. Assisting in protocol optimization to ensure consistency and quality across imaging studies. Providing
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About This Role The Resource Demand Forecasting Lead will be responsible for managing and forecasting resource needs across multiple functions in our Quantitative Sciences and Development Operations
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other constituencies. Develop and maintain supporting documentation of measurement methods and algorithms, data sources and reporting processes. Conceptualize and develop cross-functional client/unit
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motivated the development of Federated Learning (FL) [1,2], a framework for on-device collaborative training of machine learning models. FL algorithms like FedAvg [3] allow clients to train a common global
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either (a) image processing for the purpose of HIPAA de-identification and analysis or (b) training in NLP techniques and algorithms Expertise with analytics pipeline creation for combined structured
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variants, geometric algorithms like spline approaches, and optimisation-based planners. Motion planning is especially challenging for environments with multiple paths and narrow passages and for systems
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engineering systems analysis/optimization, or computational algorithms § Familiarity with multiple computer languages, including Python. § Ability to develop prototypes of tools needed to analyze data. Â
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the Budget, Financial Planning & Analysis Office using multiple reporting tools including SUNY BI, Tableau, OBIEE, and Microsoft Excel and Access. This is a dynamic role that will provide the candidate
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techniques for warehousing and accessing critical information. Recommend and implement tools and algorithms to generate reports and visualization dashboards using appropriate best practices, statistical