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Field
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W3 Endowed Professorship for “Hemodynamic Modeling in Atherosclerosis- (f/m/d) KSB Foundation W3 end
state-of-the-art imaging techniques with software-supported analysis of flow dynamics and mathematical modeling for the precise characterization of hemodynamic mechanisms in atherosclerosis. In research
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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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cooperation partners in their research projects with state-of-the-art light and electron microscopes (https://www.leibniz-fmp.de/cellular-imaging ). We work with proteins, cell cultures, and model organisms
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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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, 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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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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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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Your Job: The PhD project is methodologically independent and embedded in a multidisciplinary research environment at the interface of artificial intelligence, scientific imaging, and materials
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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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, computer science or mathematics (or a related field), with a focus on computer vision, image processing, or machine learning Solid mathematical and physics background, distinct analytical skills Very good