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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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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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, 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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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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organizational levels of the brain – from molecular and cellular processes to complex neuronal networks and behavior. The research group “Behavioral Neuroscience” focuses on decoding the exact mechanisms behind
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and experience with in vivo imaging (2-photon, miniscope, or wide field). • Good knowledge of neural data analysis and solid programming skills (preferably in Python). • Prior knowledge
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cellular processes to complex neuronal networks and behavior. The research group “Behavioral Neuroscience” focuses on decoding the exact mechanisms behind the negative consequences of sleep deprivation. We
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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