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science/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
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for catalysis of sustainable chemical processes. Visualizing Chemical Dynamics in Real Time Apply advanced atomic-resolution imaging and image analysis to uncover surface dynamics, reactivity and molecular
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learning, deep learning, and LLM-based methods to multimodal clinical datasets e.g. EHR, imaging, omics, sensor data Designing and implementing NLP pipelines for clinical text processing, semantic annotation
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Differentiate iPSCs into midbrain dopaminergic neurons and organoids for phenotyping and compound testing High content imaging and automated image-analysis Analyze omics data Collaborate closely with
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the Clinic for Radiology. As one of Germany's leading university radiology departments, we provide all outpatients and inpatients at UKM with state-of-the-art diagnostic imaging and image-guided therapy
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(https://www.cliccs.uni-hamburg.de/about-cliccs/cliccs-ll.html ). In CLICCS-M4, we are further developing the unique ICON-Coast model within the ICON Earth System Modelling Framework. The objective
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advanced molecular and cell biological techniques, including variant screening, RNA expression analyses, immunofluorescence microscopy, and transmission electron microscopy Collecting and processing patient
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language processing Develop and curate multimodal, multilingual resources for low-resource languages Design, implement, and evaluate methods that leverage multimodal signals, such as images and speech, to improve
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provide detailed insights into the atomic-level processes. By linking mechanistic understanding at the atomic scale to system-level performance, this project aims to establish design principles that can
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microscopy, microscopy, light sheet fluorescence microscopy) and flow cytometry is an advantage Confident handling of Microsoft Office (Excel, PowerPoint, etc.) and image processing software (e.g. ImageJ