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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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Max Planck Institute for Human Cognitive and Brain Sciences • | Leipzig, Sachsen | Germany | 1 day ago
opportunities for cutting-edge research projects. Students benefit from the extraordinary infrastructure enabling all types of cognitive neuroimaging experiments. The IMPRS CoNI covers all major imaging and
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the imaging system for generating image datasets from agricultural machines Develop and implement computer vision algorithms for plant disease detection and health estimation in soybeans Design and
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The molecular biosciences are undergoing a major paradigm shift – away from analysing individual genes and proteins to studying large molecular machines and cellular pathways, with the ultimate goal
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. Advanced training modules: Choose from practical courses and lecture series on topics like image analysis, microscopy, biostatistics, developmental biology, and more. Community & collaboration: Take part in
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to research solutions and to transfer our knowledge to society. We are doing this according to our vision: “Taking the pulse of our Earth to safeguard a habitable planet”. For section 2.2 Geophysical Imaging
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provide a dynamic environment which empowers excellence with state-of-the-art technologies, cutting edge infrastructure, and a global scientific network. Contribute your knowledge, vision, and dedication
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Max Planck Institute of Animal Behavior, Radolfzell / Constance | Radolfzell am Bodensee, Baden W rttemberg | Germany | about 2 months ago
ecology, evolutionary biology, molecular biology, quantitative behavior, computer vision, and physics of behavior. We envision this project to primarily involve laboratory-based investigations, although
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and phenotyping for sustainable crop production with the vision to transform crop production by optimizing breeding and farming management through developing and deploying new technologies. Within
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areas: scientific programming and data analysis (e.g., Python, R, C++, MATLAB), computational modeling, imaging and sensor data processing, bioinformatics, systems biology, or biophysics Familiarity with