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Description Post-Doctoral Fellow Position in Medical Image Processing (Deep Learning for Trauma CT) The Trauma Radiology AI Lab (TRAIL) in the Department of Radiology & Nuclear Medicine at the University
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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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programming language (preferable: MATLAB or Python) Experience with one or several of the listed human neuroscience techniques. Ability to work and learn independently and perform research with a high level of
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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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interpretable deep neural networks is required. Candidate must have published in top journal and conference at least one scientific paper in interpretable machine learning (not explanations of black boxes) among
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faculty member in the Center for Bioinformatics and Quantitative Biology (CBQB) at UIC. The successful candidate will conduct computational research at the intersection of AI/deep learning, bioinformatics
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in research and development of sustainable energy conversion technologies. We are recognized as global leaders in this field, supported by state-of-the-art facilities and deep expertise. Our
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genomics, virtual cell models Graph-based neural networks, optimal transport Biomedical imaging, deep learning, virtual reality, AI-driven image analysis Agentic systems, large language models Generative AI
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learning methods. Develop deep learning architectures (e.g., variational autoencoders, graph neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view
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, and deep learning. A Ph.D. in Statistics, Mathematics, CS/EE (with a focus on statistics/machine learning) or a directly related field at the time of appointment is required. The successful applicant