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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Developing new machine learning
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electrophysiology data obtained through collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in
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project “Analytics for Learning with Machines” (ALMA) The position is TV-L E13, 75%, limited to 3 years, funded by the Deutsche Forschungsgemeinschaft (DFG). The project is a Franco-German collaboration
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to imagine novel task configurations and learn robust manipulation policies from just a few real demonstrations. You will work at the intersection of 3D computer vision, physical simulation, and robot learning
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to take part in the supervision of PhD students and the teaching activities of the research group. Your network and team Currently, our research group consists of 1 professor, 1 lecturer, 1 staff scientist
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such as Machine Learning, Natural Language Processing, AI in Education, Knowledge Representation, and Python-based analytical seminars at the BSc, MSc, and PhD levels. Responsibilities include assisting in
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limited to, Physical Therapy, Functional Human Anatomy, Motor Learning and/or other courses as determined by Chair. Position Status Part Time Posting Number 26FA0251 Posting Open Date Posting Close Date
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research. You will strengthen the data science and machine learning activities of IAS-9 by developing core AI methods with applications to electron microscopy and materials discovery. You will work in a team
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Website https://www.academictransfer.com/en/jobs/358703/phd-in-scalable-safe-ai-for-sem… Requirements Specific Requirements A master’s degree AI, Machine Learning, Data Science, Computer Science or a
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to significantly extend our existing team’s capabilities for data scoring and analysis (e.g., with expertise in natural language processing, machine learning, or computational modeling). Finally, the