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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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postdoc position (with a possible extension for 1 more year) to lead cutting-edge research in remote sensing and deep learning as part of the Ethio-Nature project, a major international research
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leverage state-of-the-art deep learning techniques to address challenges in visual data processing and forensic analysis. As part of a dedicated, collaborative research team, you will push the boundaries
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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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Your profile Candidates should have an exceptional academic record and a robust mathematical foundation. They should have published works at the main conferences in the field of machine learning
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 33 minutes ago
wildland-urban interfaces— across a wide range of climate conditions. Using machine learning methods, we will optimize the weightings of each contributing factor and identify the key drivers of wildfire risk
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Job DescriptionPosition: Postdoctoral FellowTopic: Reinforcement Learning for Vortical Flow Control and Sensing. Requirements: 1) Age under 35. 2) Ph.D. degree (obtained or about to obtain) in
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Job DescriptionPosition: Postdoctoral FellowTopic: Reinforcement Learning for Vortical Flow Control and Sensing. Requirements: 1) Age under 35. 2) Ph.D. degree (obtained or about to obtain) in
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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