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and in silico. We focus on neurodegenerative processes and are especially interested in Alzheimer's and Parkinson's disease and their contributing factors. The LCSB recruits talented scientists from
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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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13C incubation approaches the current project will quantify dark carbon fixation rates in deep ocean settings and explore how environmental parameters affect the process rates. These approaches
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of: Perform advanced microstructural and topological analysis of natural fibres using 3D imaging and image‑processing tools. Design and refine routes to isolate and tailor lignin fractions derived from
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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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-throughput experiments in molecular biology, image and video analyses as well as pattern recognition of complex public health data Collaboration in the development of algorithms/methods and development
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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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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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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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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