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and assessing weld quality of mechanical parts in real-time by developing machine learning models that use sensor data and other tasks that are assigned to you. Core Responsibilities: Understanding
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Summary: Duke University is a world-renowned research institution. Currently, we are looking for a Postdoctoral Associate with expertise in deep learning to participate in a research program focused on
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-scale human datasets. You will: - Build and apply machine learning and deep learning models to multi-scale (cells, brains, patients), multi-modal (omics, biosensor data, vision, electronic health data
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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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. Conduct transportation resilience assessment and enhancement studies based on GIS, complex network analysis, and machine learning. Simulate human mobility in response to extreme weather events (e.g
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. The project focuses on the intersection of deep reinforcement learning, probabilistic modeling, and bio-inspired architectures (such as Spiking Neural Networks) to achieve sample- and energy-efficient robust
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trials and deep learning-based modeling of multimodal biomedical data. We are seeking two highly motivated scientists with expertise in Causal Inference / Statistics / Deep Learning / Bioinformatics
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graphics, machine learning and graphics programming, as well as a good command of English. Knowledge of data science and deep learning is an advantage. You demonstrate good team spirit, interpersonal and
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: A doctorate in a Machine-Learning related field A deep knowledge of Control Theory, both classical and deep learning based A solid publication record in top level ML venues such as NeurIPs, ICML, and
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Job Description Here's a Glimpse of the Job The Postdoctoral Research Associate will be involved in developing deep learning architecture for multi-object data integration, federated learning approaches