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and simulation aspects across a wide range of fields - from biomechanics and geophysics to polymer-fluid coupling. Further areas of interest include numerical algorithms for high-dimensional problems
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smart grid). While there has been tremendous progress in formal verification of cyber-physical systems, existing approaches still require expert knowledge. The main goal of this project is to develop
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data analysis and develop sophisticated mathematical models for simulating power system behaviors under various scenarios. Development and Testing: Design and develop control algorithms to enhance grid
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efficient algorithms and machine learning/artificial intelligence methods in combination with complex network analysis tools to predict and model interactions between food and biological systems • Further
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: • Mathematical derivation, analysis, and comparison of models, methods, and simulation approaches. • Rapid prototyping of new ideas in custom code. • Implementation of new models, methods, and algorithms
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research studies for automated image analysis. In particular, you will: Plan, develop, and implement AI/ML algorithms for pathology image analysis. Integrate multi-modal data (e.g., genomics, clinical data
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and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods
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and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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processing workflows including QC and reproducibility metrics * APIs and packages supporting the development of new algorithms spanning large * language modeling of DNA and RNA sequences, and algorithms