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Abrahao (NYU Shanghai) and João Sedoc (NYU Stern). Research Focus Areas Our research encompasses topics in DL and AI, including but not limited to: Deep Learning Algorithms and Paradigms Generative Models
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Responsibilities: To conduct independent research in deep learning and large language models. To produce publications in top conferences and journals. To offer guidance and assistance to any students involved in
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-campus for the Fall 2025 Semester (09/02/2025 - 12/14/2025) Course: Deep Learning This course covers the theory and practice of deep learning, including neural networks, convolutional networks, and
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the internationally renowned INTERGROWTH-21st Consortium. This role involves developing advanced deep learning techniques to identify early indicators of fetal vulnerability using clinically-acquired ultrasound (US
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deep reinforcement learning (DRL) methodologies for both gene-level and edge-level perturbation control, represents a significant advancement in the computational toolkit for cellular reprogramming
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Ine-Therese Pedersen 15th August 2025 Languages English Norsk Bokmål English English PhD position in Deep Learning for Metocean Data Apply for this job See advertisement About us We are announcing a
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computational framework, integrated with deep reinforcement learning (DRL) methodologies for both gene-level and edge-level perturbation control, represents a significant advancement in the computational toolkit
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architectures for deep learning. Deploy your models onboard robotic systems. Publish your findings at top-tier venues. Disseminate your research findings at national and international workshops and conferences
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or infrastructure. This is what makes our daily work so meaningful and exciting. The Division of Computational Genomics and Systems Genetics is seeking from October 2025 a PhD Student in Deep Learning for Rare
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-aware multi-modal deep learning (DL) methods. At Argonne, we are developing physics-aware DL models for scientific data analysis, autonomous experiments and instrument tuning. By incorporating prior