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Networks, and ICT Services & Applications. Your role Design intelligent agent architectures leveraging large language models (LLMs), planning algorithms, and secure transaction protocols tailored
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experimentation with Asst. Prof. Eli N. Weinstein. Your goal will be to develop fundamental algorithmic techniques to overcome critical bottlenecks on data scale and quality, enabling scientists to gather vastly
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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Leibniz-Institute for Plant Genetics and Crop Plant Research | Neu Seeland, Brandenburg | Germany | about 1 month ago
related to staff position within a Research Infrastructure? No Offer Description The Quantitative Genetics research group is interested in developing statistical genomics toolboxes to decipher the genetic
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. Experience in applying or developing machine learning
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consumption while guaranteeing optimal power production. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop graph-based
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Aerospace Centre (DLR), will conduct research on 20 research topics with 25 PhD candidates within the next years. The following main research goals are pursued by this Center: (1) develop a new set of
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. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data analysis. For more
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. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data analysis. For more