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-varying photogrammetry 3D point clouds of growing plants for high throughput phenotyping applications. A key part of the project is to craft training data for a Deep Learning-based method aimed
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) faculty are committed to enhancing student success by engaging students in quality academic instruction, research, internships, global studies, and other experiential learning opportunities. There is an
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) faculty are committed to enhancing student success by engaging students in quality academic instruction, research, internships, global studies, and other experiential learning opportunities. There is an
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university located in the heart of Detroit, Michigan where students from all backgrounds are offered a rich, high-quality education. Our deep-rooted commitment to excellence, collaboration, integrity
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networks for deep learning on dynamic graphs. arXiv preprint. Trantas et al (2023). Digital twin challenges in biodiversity modelling. Ecological Informatics. Borowiec et al (2022). Deep learning as a tool
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or experimental research involving passive, active, specialty, or telecommunication optical fibers, or in modeling linear and nonlinear phenomena—including the use of deep learning methods—in the field of optical
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connection with the legal adoption of an eligible child, such as travel or court fees, for up to two adoptions in your household. To learn more, please visit: https://www.hr.upenn.edu/PennHR/benefits-pay
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) Develop AI‑driven model calibration by designing a deep‑learning pipeline mapping data extracted from experiments onto force fields and use these predictions to initialise Cytosim simulations. (3) Use
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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(e.g. Large Language Models and Deep Learning architectures for Explainable AI, Agentic AI, Neuro-symbolic AI and Reinforcement Learning) with connections to Natural Language Processing, who will