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University System of Georgia leadership institution and is The Military College of Georgia. More details on the UNG Mission, Values, Vision, and Culture can be found at https://ung.edu/about/mission-vision
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clinical features using machine learning and foundational modeling approaches. This work supports disease modeling across chronic kidney disease, acute kidney injury, cancer, and neurological conditions. A
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; Distributed multi-agent sensing and cooperative positioning algorithms; Machine learning and data-driven methods for ambient awareness. Working Environment: The PhD will be conducted at the University
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(https://www.hsph.harvard.edu/lin-lab/ ), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods
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yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in
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Your Job: Investigate current challenges and bottlenecks in power flow analysis for large scale electrical distribution grids Apply machine learning/AI or surrogate modeling (e.g., neural networks
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evidenced by a strong publication record in one or more of the following areas: random matrix theory, stochastic processes, neural networks, machine learning, and sparse data structures • Proficiency in
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analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
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alloys for energy applications in harsh environments using additive manufacturing. This research involves integrating computational modeling, machine learning, and experimental investigations to design and
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identification in greenhouse environments. Apply machine learning to analyze plant and environmental data. Support the integration of AI algorithms with automated sensing systems for real-world deployment. Assist