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Field
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communication protocols to support data sharing across multiple agricultural sites using networked edge devices. Develop AI algorithms for distributed deep learning that optimize training time and ensure data
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to develop and sustain a research program focusing on any area related to cybersecurity, formal methods, algorithms, and/or artificial intelligence, including but not limited to: usable security and privacy
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Technician - Dept of Neurobiology & Behavior (CAS) - Technician II The Fernandez-Ruiz & Oliva labs employ a multi-disciplinary approach, including the development and application of cutting-edge experimental
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Duke Kunshan University Position ID: DukeKunshanUniv -25SNASCOMPSCI [#29608] Position Title: Position Location: Kunshan, Suzhou 215316, China [map ] Subject Areas: Computer Science / Algorithms
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to Neuroimmunology and Multiple Sclerosis. Our department provides translational science expertise to inform the clinical development of novel personalized therapeutics, and our biomarker teams investigate
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to integrate large and complex molecular datasets with information at individual level, with specific attention to open and reproducible research, e.g., in the development of codes and algorithms. We will focus
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analyses, develop diagnostic, prognostic, and predictive models using different types of data (e.g., exposure data, omics data, and clinical data), and develop algorithms and methodologies for evaluating
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Digital Twin for electric vehicle applications . The role will focus on utilizing novel machine learning models, large language models, and data science algorithms to develop battery models, optimization
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of computational biology and bioinformatics; Research and stay current with project related scientific literature; Develop and validate new algorithms and tools to accomplish scientific objectives; Identify and
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on available work, funding, and performance. Anticipated Division of Time (30%) Direct research program in AI/ML applications for climate science, including supervising team members, developing novel algorithms