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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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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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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
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Deadline : April 15th 2026 · Selection Process : Mai 2026 · PhD Start Date : September-October 2026 How to apply All information are provided on the website of the project : https://www.eu4greenfielddata.eu/
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research environment. You should have prior experience with experimental molecular biology techniques, tissue processing and imaging. You also have strong technical and analytical skills. Previous experience
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of living cells and single-molecule visualization of proteins, providing new insights into biological processes. Applied research targets cancer diagnosis and treatment, leveraging nano-imaging technologies
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The AITHYRA-CeMM Joint International PhD Call in Molecular Medicine and Artificial Intelligence (m/f
-20 fully funded PhD positions here: https://apply.cemm.at/ Supported by the Medical University of Vienna, the Technical University of Vienna and University of Vienna, the AITHYRA and CeMM PhD programs
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to the success of the whole institution. Biomolecular condensates have emerged as a new paradigm to understand biological functions in living cells. Dresden has pioneered research in the field of biomolecular
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& Machine Learning • Clinical pathways and decision support for patients with acute chest pain • AutoPiX – Explainable Deep Learning for Multimodal and Longitudinal Imaging Biomarkers in Arthritis • Speaking
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can be used as a therapeutic target to treat human diseases. In this context, one key methodology that we are using is constraint-based metabolic modelling approaches. Start in our team: We are looking