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Field
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theory and experiment. By integrating quantum optics, quantum information theory, and machine learning, the project seeks to establish scalable hybrid spin–orbit quantum links. Free-space connections
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: Data Mining Machine Learning Bioinformatics The successful candidate will contribute to advancing state-of-the-art in data mining and machine learning research with applications in computational biology
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Degree PhD Learning Sciences (alternatively Dr phil, Dr rer nat, Dr med; not recommended for international students) Course location München Teaching language English Languages Courses are held
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analysis, has good software skills (Python, C++, ROOT) and has (some) research experience in experimental particle physics. Experience with machine learning algorithms and software is desirable but not
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, target recognition and shape estimation, data association, as well as intention prediction, beyond the state of the art. In order to support machine learning, the project will make use of historical radar
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will include boosted final states. The analysis strategy is strongly focused on advanced machine learning techniques, developing attention-based transformer models that will directly classify events from
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to improve detection capabilities, target recognition and shape estimation, data association, as well as intention prediction, beyond the state of the art. In order to support machine learning
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and programming (MATLAB, Python, R, or other scientific coding/programming). Affinity with computational neuroscience, connectomics and/or Machine Learning is appreciated. Our goal perform connectome
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, work and participate in democracy, our centre tackles the promise and peril of hybrid intelligence—human and machine working and learning together. AI LEARN’s mission is to establish an internationally
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and implementing innovative solutions at the intersection of sensor data collection, machine learning, and real-time decision-making. Specifically, the candidate will contribute to projects focused