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University of São Paulo, Brazil. This position focuses on developing advanced computer vision methods and hardware setup for detecting and predicting plant diseases in soybean cultivation. About Us The Chair
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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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institution. At the Faculty of Computer Science, Institute of Artificial Intelligence, the Chair of Machine Learning for Computer Vision offers two full-time positions as Research Associate / PhD Student (m/f/x
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, please visit: https://qbm.genzentrum.lmu.de/application/ Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content
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16.02.2026 Application deadline : 15.03.2026 The Collaborative Research Center (CRC) 1233 “Robust Vision” brings together leading researchers in machine learning, computer vision, and systems
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Degree PhD in Neuroscience Course location Bochum Teaching language English Languages Courses are held in English. Full-time / part-time full-time Programme duration 6 semesters Beginning Winter
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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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well as an active engagement in the 3RTG activities. Requirements: successfully completed university degree (Master's, Diploma or equivalent) and relevant PhD in Computer Science, Computer Engineering, or related
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Max Planck Institute of Immunobiology and Epigenetics, Freiburg | Freiburg im Breisgau, Baden W rttemberg | Germany | 5 days ago
approaches in the lab Develop original research ideas aligned with the lab’s vision Guide and supervise students (from Bachelor’s to PhD level) Present research findings at lab meetings, institute seminars
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science, data science, applied mathematics, physics, materials science, or a related field. Solid background in machine learning and/or computer vision. Interest in representation learning, active learning