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Field
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will provide deep, high-resolution near-infrared imaging of far more area than ever before possible. Roman’s launch is expected in the fall of 2026, making this project well timed for delivering
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learning on graphs, including knowledge graphs, social and biological networks, financial networks, temporal and dynamic graphs, uncertain graphs, explainability and fairness of deep learning methods
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students. Qualifications: Required: PhD in Computer Science, AI, Data Science, Statistics, or related. Strong skills in machine learning and deep learning, with a fundamental understanding of LLMs
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models. Experience in large-scale deep learning systems and/or large foundation model, and the ability to train models using GPU/TPU parallelization. Experience in multi-modality data analysis (e.g., image
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, Statistics, or related. Strong skills in machine learning and deep learning, with a fundamental understanding of LLMs. Proficiency inPython programmingand major ML/DL frameworks (e.g., PyTorch, TensorFlow
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-Service (MaaS) ecosystem. The work will integrate deep reinforcement learning, autonomous agent modelling, and multi-objective optimization to enable predictive simulation, real-time resource management
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, Greninger Lab Position Details Position Description The Greninger Lab at the University of Washington is seeking a Postdoctoral Scholar driven by curiosity, eager to dive deep, think big, and learn fast - a
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Are you passionate about deep learning, generative AI, agents? We are seeking a postdoctoral researcher to join the research group led by Ivan Titov ( http://ivan-titov.org/ ), part of the natural
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to the academic environment through teaching and supervision activities. If you enjoy combining deep scientific questions with computational innovation—and want your work to support the future of sustainable
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of the appointment. Demonstrated experience with deep learning methods or sophisticated mathematical frameworks applied to large-scale or scientific datasets. Experience working with observational seismology data (e.g