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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
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scientists, and researchers working on medical image analysis, machine learning, and audiology. Our recent work has focused on using deep learning to analyse temporal bone CT scans and brain MRI data in
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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
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supported by an external team of deep-learning experts. You will also become an integral part of the Multiscale Cloud Physics Group currently being established by Dr Franziska Glassmeier at the Max Planck
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learning, at the intersection of reinforcement learning, deep learning and computer vision, in order to train effective robotic agents in simulation. You should hold a relevant PhD/DPhil (or near completion
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to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular dynamics, and materials chemistry. Strong
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new MRI techniques for motion-robust imaging, real-time image processing, and/or deep learning. The work includes MRI pulse sequence design for various MRI techniques and technologies, algorithm and
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NASA. The researcher will utilize multi-decadal satellite imagery and deep learning techniques to analyze temporal trends in urban structure and their impacts on microclimate, focusing on extreme heat
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simulations of PDEs, deep learning, neural networks. Our research interest: Our focus is on theoretical and computational biological physics, ranging from the study of molecules to cells. We strive to leverage
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learning, deep learning, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific