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concerned, among other things, with the effects of images and the mechanisms that make up communication with images. Key questions are: Who produces images and for whom? What message do these images convey
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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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that exhibit emergent turbulent behaviors, and (2) disordered optical media that process information through complex light scattering patterns. Using advanced imaging, machine learning techniques, and real-time
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disease variants, to gain insights into how cells adapt and work together to safeguard organ formation. Using advanced live-imaging techniques, the research team closely interrogates how developing tissues
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materials and evaluate various electrocatalysts develop a laboratory prototype cell setup suitable for scale-up publish results in international journals develop market for electrolyzer technology
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. The successful applicant will integrate multi-modal live imaging and omics data using AI-based pipelines to identify and refine early disease phenotypes, laying the groundwork for therapeutic intervention
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, functional MRI, diffusion-weighted imaging, and EEG, in combination with genetic data (GWAS, bioinformatics) from large-scale population cohorts. Positioned at the intersection of biological psychology
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between the fields of computer sciences and architecture. The focus lies mainly on Building Information Modelling, decision-support methods in urban planning and knowledge-based design methods. As part of
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The »High-Performance Cutting « department develops technologies and application-oriented solutions for machining along the entire process chain - from process design and process simulation to real
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and/or atom probe tomography Experience in image processing Experience in programming with Python or Matlab is strongly desired Team spirit as well as excellent communication and organizational skills