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Field
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is a world leader in research into mobile and optical communication networks and systems as well as the coding of video signals and data processing. We are looking for student assistants
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using Multimodal AI models as per the preference of the student. What you bring to the table PyTorch, Multimodal AI, Gaussian-Splatting, Image Processing (AI Approach). OR Experience with loading and
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Your Job: Combine multimodal brain imaging with advanced image-processing, data science, and AI techniques to perform image alignment, segmentation, and classification to construct and validate
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to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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Medical Imaging (IBMI) at Helmholtz Munich and the Chair of Biological Imaging (CBI) at the Technical University of Munich (TUM) are an integrated, multi-disciplinary research unit. Together they form
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, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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real-time during behavioural tasks Integrating virtual reality paradigms with behaviour and imaging to assess decision-making processes Exploring potential therapeutic interventions for NMDA receptor
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discovery and chemical ecology. We also envisage to perform complementary spatial metabolomics using the in-house Desorption Electrospray Ionization-Imaging Mass Spectrometer (DESI-IMS). The candidate will
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cells (e.g., immune cells and tumor cells) in OoC systems Performing imaging experiments using light and fluorescence microscopy Quantitative image analysis and evaluation of immunological responses