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at the Faculty of Medicine, University of Helsinki. The project will focus on using and extending deep learning-based approaches developed within the group to integrate bulk multi-omics cancer data. The Kuijjer
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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
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relevant field at the PhD level with zero to five years of employment experience. Experience with deep learning frameworks (PyTorch, TensorFlow, JAX). Strong background in computational image processing and
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Post-Doctoral Position in Deep Learning for MRI Reconstruction at Yale University Title: Postdoctoral Associate, Yale School of Medicine Department/Division: Radiology and Biomedical Imaging
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We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling to join the Oxford-Novartis Collaboration in AI Medicine team at Nuffield
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An exciting postdoctoral position is available in the exciting field of mathematics of deep learning, under the joint supervision of Prof. Alex Cloninger and Prof. Gal Mishne at UC San Diego. This NSF-funded
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-accelerated iterative optimization strategies and deep learning-driven approaches. We are looking for a candidate with an interest in applying optimization and machine-learning techniques to solve real-world
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Postdoctoral Affairs. The FY25 minimum is $76,383. Position is FILLED The Stanford Optima Group is seeking a highly motivated and skilled postdoctoral researcher to lead machine learning projects investigating
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rules which enable effective learning in large and deep networks and is consistent with biological data on learning in the cortex. In particular, the research will focus on evaluating and extending a
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We are seeking a full-time Postdoctoral Research Assistant to join a cross disciplinary research project to improve our understanding of colorectal cancer. Deep learning has revolutionised image