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Field
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responsibilities include: Development of a flood classification framework for flood type prediction Comparison of different ML algorithms in a sensitivity study Communication with stakeholders Development of open
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learning and one PhD student with a keen interest in the algorithmic side of hyperbolic deep learning. Tasks and responsibilities: Conduct high-impact research on hyperbolic deep learning for computer vision
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science and societal application. We contribute to innovative information technologies through the development and application of new concepts, theories, algorithms, and software methods. With our expertise
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in basic control-flow analysis. Process mining, as it stands today, is primarily based on computational techniques and algorithms to analyze and optimize processes. Methods such as process discovery
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of both science and societal application. We contribute to innovative information technologies through the development and application of new concepts, theories, algorithms, and software methods. With our
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of hyperbolic deep learning and one PhD student with a keen interest in the algorithmic side of hyperbolic deep learning. Tasks and responsibilities: Conduct high-impact research on hyperbolic deep learning
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or incomplete. Information Your tasks will include: Developing and benchmarking ML/AI algorithms tailored to low-data regimes — e.g. few-shot learning, transfer learning or data-efficient representation learning
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the entire system, where many interconnected modules affect each other. In this project, you will be designing algorithms to guarantee the reliable operation of semiconductor machines, together with a highly
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tagging algorithm development as well as physics data analysis, with a focus on Higgs boson physics, top quark physics, and searches for new physics signatures. This is what you will do After the discovery
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, enabling energy-efficient, quiet, and long-duration monitoring of ecosystems. The research will integrate novel lightweight perception modalities for robust perching in the wild, agile control algorithms