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-facing web GIS dashboard. Investigate the forest, landscape, and climate conditions that drive storm susceptibility, using major windstorms as natural experiments and interpretable machine-/deep-learning
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Associate Research Scientist / Post-Doctoral Associate in the Division of Science (Computer Science)
, seeks a Post-Doctoral Associate or a Research Associate to join a lab focused on applied machine learning. The successful applicant will participate in research involving human computation, knowledge
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(payable 14 times per year) Responsibilities The applicant is expected to establish an own research group with focus on advanced machine learning and deep learning techniques for remote sensing applications
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. The project will involve drone optimizations, computer vision, closed-loop control, multi-modal sensor fusion, machine learning, and transfer learning methods. The candidate will also work in collaboration with
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, depression and substance abuse. This knowledge will facilitate the development of orexin-based therapies that can effectively treat the multifaceted symptoms associated with this neural system. This Post Doc
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methods, including amplicon or shotgun sequencing. Experience with axenic/gnotobiotic rearing. Certifications/Licenses Required Knowledge, Skills, and Abilities Preferred Qualifications Mosquito colony
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methods with the ability to implement and evaluate machine-learning systems at scale. Candidates may come from topological data analysis, geometric deep learning, network science, statistical physics
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across a range of application areas, including education and healthcare. As these systems are increasingly deployed in high-stakes environments, there is a growing need for machine learning models
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for Transportation (VITA ) is looking for a postdoctoral researcher in the area of Generative AI. VITA research interests lie at the intersection of Computer Vision, Machine Learning (Deep Learning), and Human-Robot
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Learning: Apply shape-correspondence and machine-learning approaches, including spectral/graph-based surface alignment and autoencoder-based shape extraction, to compare limb and joint morphology across