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Field
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developing an AI machine learning algorithm to analyze how experimental parameters ( 3D printing and electrospinning) affect the design. Work with PhD students in data collection (physical and mechanical
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, research website maintenance, clinical coordination in experiments, group meeting minutes organization Aiding in developing an AI machine learning algorithm to analyze how experimental parameters ( 3D
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only within dense, highly interacting systems, inaccessible to standard techniques. To probe such regimes requires the development of fast and scalable algorithms for many-component systems, and of
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Scientific Machine Learning. The successful candidate will develop and deploy state-of-the-art SciML algorithms in high-performance computational physics codes. We accept applications from all candidates with
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research involving biological data analysis and modeling of biological systems. In particular, they will develop and apply algorithms to construct discrete dynamic models of signal transduction networks
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, research website maintenance, clinical coordination in experiments, group meeting minutes organization Aiding in developing an AI machine learning algorithm to analyze how experimental parameters ( 3D
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to actively drive research projects to predict clinically important endpoints using your knowledge in algorithm development. You will be part of a growing, interdisciplinary team and join weekly
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for study sessions and documentation of experimental results. Job Description Primary Duties & Responsibilities: Assists research studies with implementation of: existing algorithms and computer software for
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learning algorithms into professional software with an intuitive user interface, incorporating feedback from CHWs through iterative design and evaluation cycles. The selected candidate will be part of a
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electronic systems with a focus on inverters and active filter-based harmonic mitigation, thermal performance, and control strategies. Develop and implement advanced control algorithms for real-time operation