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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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basic research neurobiology lab at the Free University in Berlin Germany. The main focus of the lab is the study of how genomic information 'unfolds' to develop neural networks with remarkable information
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often represented in large neural networks that are hard to analyze and whose decision processes cannot be interpreted by humans. To make this technology available without sacrificing safety concerns, we
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, clustering, neural networks) for spectral interpretation, segmentation, and material identification. • Create and curate a dedicated HSI spectral library for cultural heritage materials, linking reference
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academic, clinical, and industry partnerships, as well as global networks, we translate biological insights into innovations for early detection, individualized therapies, and disease prevention. Founded in
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intelligently to make learning more sustainable and efficient, and a DFG-funded project on distributed optimization and scalable training of deep neural networks, including transformer architectures. We invite
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questions in the areas of self-supervised/label-efficient learning and explainability of deep neural networks (XAI) are being developed, particularly for use in biomedical applications. Further information
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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | 3 months ago
electrophysiology, functional imaging, or light/electron microscopy Familiarity with genetic and molecular biology tools Background in computational modeling of neural systems A demonstrated ability to secure
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models and neural networks that handle the many challenges of integrating such complex medical data sources on large-scale studies and the translation to clinical practice. Qualifications PhD in (Bio
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(ML4Earth). AI methods, and especially machine learning (ML) with deep neural networks have replaced traditional data analysis methods in recent years. The Technical University of Munich (TUM), together