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geological modelling and/or geophysical imaging Familiarity with site investigation, borehole logging, and geophysical approaches Experience with machine learning or deep learning is preferred Good written and
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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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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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for supervised and unsupervised learning. We devise deep learning models, which find application in imaging and image-based science, including in collaboration with domain scientists on and off campus in fields
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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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, social learning, intrinsic activity, and predictive coding. We are now seeking highly motivated and enthusiastic postdoctoral fellows (project researchers) or project faculty members to work under the
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with deep generative models (VAEs, GANs, diffusion models) or probabilistic modelling is a strong plus. You have good programming skills in Python and experience with a deep learning framework such as
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 2 months 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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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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As a postdoctoral researcher, your primary responsibilities will be: Develop machine learning and deep learning models, with a strong focus on computer vision, for the characterisation and