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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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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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. Here you partly work on your tasks on-site in our institute/ machine park. What you will do Analyze acquired microscopic and video tool wear data Investigate image processing techniques such as spatial
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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) manual annotation of audio, video and images What you bring to the table The following skills are required: experience with algorithm development in Python knowledge of digital signal processing, machine
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) manual annotation of audio, video and images What you bring to the table The following skills are required: experience with algorithm development in Python knowledge of digital signal processing, machine
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within the Clusters of Excellence ‘Machine Learning for Science’ and ‘Image-Guided and Functionally Instructed Tumor Therapies (iFIT)’. Requirements PhD in Bioinformatics, Computational Biology, or a
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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Neurobiologie (ZMNH) Main tasks You will join the Institute of Medical Systems Biology and the bAIome Center for Biomedical AI (baiome.org) to complement our lively and enthusiastic team of machine learning and
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Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning