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. Education and scholarly development The postdoctoral associate will receive structured education in computer vision applications in medical imaging, machine learning, research methodology, responsible conduct
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and qualifications Expertise in advanced machine learning, deep learning and image vision techniques with focus on EO data (e.g. deep convolutional neural networks, transformers, deep learning based
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Science, Biostatistics, or a closely related area. Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP. Demonstrated working experience
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Development of reproducible software tools and computational workflows for biomedical research Develop novel AI, machine learning, and deep learning methods to address complex biomedical questions in diabetes
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completed a postdoctoral contract of at least 2 years and have advanced research experience in the field of microscopy and image analysis. You are an expert in cryo-electron microscopy and image analysis. You
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
-driven technologies for biomedical research and cancer diagnostics Your profile Master's degree in a relevant field Experience in machine learning for imaging, ideally in biomedical or histopathological
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or deep learning reconstructions). Knowledge of radial data acquisition strategies, artifact mitigation methods, and their use in parametric imaging (e.g., T1/T2/T2* mapping). Preferred Qualifications
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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
but are not limited to: development of new AI architectures for biology and hybrid models that combine deep learning with mechanistic models; foundation models of genome regulation using single-cell and
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theoretical advances into practical insight and tools that can support analysis, design and decision-making for AI-enabled space systems, thereby bridging the emerging scientific theory of deep learning with
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ability to acquire competitive funding. Interdisciplinary mindset and keen on collaborating broadly in the center, the department and the university. Motivated to guide postdoctoral researchers, PhD interns