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automated configuration mechanisms based on fingerprinting and machine learning to ensure traffic analysis remains faithful to the behavior of the monitored machines. Finally, you will validate your solutions
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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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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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on the problem of making distributed machine learning robust to network outages and computational bottlenecks. The work is part of the Norwegian national AI centre SURE-AI, and the PhD student will
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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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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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(GME) training programs, as well as other National Institutes of Health T32 training programs and associated graduate programs. The appointee will partner with MCB and GME faculty to develop and co-teach
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associate will be assigned, as well as upon the specific needs of the faculty member in charge of the course: Instruct and manage the classroom Create or implement course design and assignment sequence
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LevelPhD or equivalent Skills/Qualifications PhD (or equivalent) in mathematics or computer and information sciences or information and communication technology, at least 2 years of documented experience in
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Shifting the paradigm: machine-assisted scholarly digital editing Digital Humanities Institute PhD Research Project Self Funded Dr Isabella Magni Application Deadline: Applications accepted all year