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Field
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deep learning methods for multi-modal image data applied to industrial challenges in the energy sector? Advance the use of seismic tiles for extracting information about geological layers? Contribute
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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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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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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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. 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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, and finally using deep learning to solve the complexity challenge associated with coherent beam combination. The role Within HiPPo, your specific task will be to develop a ‘digital fibre laser’, through
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depends on the background of a suitable candidate. The main topics of the group in the past few years were generative modeling, 3D reconstruction, image-editing, and deep learning using 3D data. More
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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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including functional enrichment (GO, KEGG), network analysis, genome assembly and binning, systems biology, and multi-omics integration. Apply statistical modelling, machine learning, and deep learning
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to develop deep learning models for analyzing whole-slide histopathology images, as well as natural language processing (NLP) methods for clinical records such as pathology reports and electronic health data