71 machine-learning-"https:"-"https:"-"https:"-"https:"-"ISCTE-IUL" Postdoctoral positions in Germany
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- Technical University of Munich
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- Georg August University of Göttingen
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- Max Planck Institute for Astrophysics, Garching
- Max Planck Institute for Dynamics and Self-Organization, Göttingen
- Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg
- Max Planck Institute for Evolutionary Biology, Plön
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig
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- Max Planck Institute for Radio Astronomy, Bonn
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden
- University of Oldenburg
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strong background in image processing and analysis, including deep learning (e.g., CNNs) experience with correlative imaging workflows and 2D/3D registration techniques strong programming skills in Python
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for image-based modelling Your profile PhD in physics, materials science, computer science, applied mathematics or a related field strong background in image processing and analysis, including deep learning
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cutting-edge technologies — from single-cell multi-omics and deep learning to live-cell imaging and stem-cell–based organoid systems — to predict, observe, and manipulate epigenetic processes. Our lab and
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presentations at international conferences Willingness to learn and interest in interdisciplinary applied research We offer: A varied and challenging job within a top-class network from politics, science
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, bright individuals with a diploma or master’s degree in bioinformatics, biochemistry, biology, molecular/translational medicine or related subjects and a PhD in life and computer sciences. Previous
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | 3 months ago
experience Experience in computer programming; Experience of computational mathematics or data analysis Experience with interdisciplinary applications in biology Our offer A full—time position, with a flexible
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' to develop neural networks with remarkable information content: flies, which we use as a model, have brains that compute flying in 3D, navigation, metabolism and advanced learning and memory capabilities - all
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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into neuroendocrine output to instruct adaptive physiology and behavior. Conversely, we seek to understand how internal states shape our physiological responses to the same cues. Our research is based on the premise
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verification scalable and reliable. Learn more about logical zonotopes: [paper link ] | [talk link ]. You will conduct original research on logical zonotope based methods for model checking and digital circuit