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Fellow in Deep learning for subsurface imaging Apply for this job See advertisement About the position Position as Postdoctoral Research Fellow in Deep learning for subsurface imaging available
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Details Title Postdoctoral Fellow in Deep Learning Theory and/or Theoretical Neuroscience School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position
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models, focusing on industrial image analysis Develop advanced deep learning methods for power battery inspection models Design and implement novel algorithms for AI-based CT imaging Lead experimentation
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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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. Strong programming skills in Python, with proficiency in deep learning frameworks such as PyTorch, TensorFlow, or JAX.. We regret that only shortlisted candidates will be notified. Hiring Institution: NTU
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The DeepWave industry-funded consortium is looking for two outstanding postdoctoral researchers to undertake impactful research on the development and application of cutting-edge machine (deep
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processing, artificial intelligence, cognition and deep learning, machine learning, navigation and mapping, autonomous driving, assistive robotics, drones, dynamics and vibration, acoustics, medical imaging
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Informatics (DBMI) at Harvard Medical School and the Yu Lab are seeking a Postdoctoral Research Fellow with experience in machine learning and scientific programming. The candidate will work with a multi
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research, formulate hypotheses, and design effective experimental plans. Strong programming skills with deep learning frameworks (e.g., PyTorch). We regret that only shortlisted candidates will be notified
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the digitalization for risk management; therefore, it is expected that the candidate will be familiar with new methods such AI (deep learning) for subsurface studies (seismic interpre-tation). A part of the