1,553 machine-learning "https:" "https:" "https:" "https:" "U.S" "U.S" positions in Germany
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NEST: https://nest-simulator.readthedocs.io Your tasks in detail: Work with the NEST main code base and experimental branches Dissect the spiking network simulation cycle into phases and capture the flow
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applies), preferably via the TUD SecureMail Portal https://securemail.tu-dresden.de by sending it as a single pdf file to mlcv at tu-dresden.de or to: TU Dresden, Chair of Machine Learning
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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action recognition, and enable seamless collaboration between humans and machines. Long-Term Human-Technology Evolution: investigate the longitudinal impact of human-technology interaction on learning
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recognition, and enable seamless collaboration between humans and machines. Long-Term Human-Technology Evolution: investigate the longitudinal impact of human-technology interaction on learning, behavior, and
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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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strong Excel skills You are organized, reliable, and proactive You are a good communicator and enjoy teamwork You are comfortable working in English (at least B2 level according to the CEFR: https
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mind for learning new technologies is particularly encouraged to apply. Your Profile: We are looking for a highly motivated and enthusiastic individual with: a master’s degree, diploma, or an equivalent
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Max Planck Institute of Animal Behavior • | Radolfzell am Bodensee, Baden W rttemberg | Germany | about 17 hours ago
the University of Konstanz Teaching language English Languages The entire course is taught in English. German is not required, but it is recommended to learn the German language so as to increase integration
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strengths of the University of Tübingen in Computer Sciences and Machine Learning. Potential research directions include, but are not limited to, phylogenetic, demographic, ecological and biogeographic