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Field
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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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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with
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other equipment at the Cellular Imaging Facility Operation and quality testing of fluorescence microscopes Training and support of users of electron microscopes Laboratory management Your profile
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automation integration and deployment of image segmentation algorithms for the automated assessment of thin-film solar cell fabrication processes (e.g. layer quality, defects, morphology) within NOMAD Oasis
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Course location Hamburg Description/content The Cluster of Excellence "CUI: Advanced Imaging of Matter", which is funded by the German federal and state governments, combines projects in physics
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Matlab or experience with Python and willingness to learn Matlab are required. Experience with functional data (fMRI, calcium imaging) or image processing is a plus. Experience working with birds is not
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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time
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Package: Actively participate in a participant-driven co-design process to develop a framework for returning molecular and imaging data to study participants Contribute scientific content to patient
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collaboration, we are building a high-throughput single-cell analysis platform that combines microfluidics, advanced imaging and AI-based analysis to study gut microbial consortia. You will drive the development
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candidate will facilitate code collaboration within the Modelling of Atmospheric Processes (MOD) department and, in particular, manage IAP code contributions to the upper atmosphere components of the ICON