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Field
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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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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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, 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 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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. The objective of the research is to use machine learning methods to find models of ship trajectories and traffic patterns that can be used to detect anomalies and predict into the future. The basis for this is
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related to Computer Science, Machine Learning, Data Science, Information Management or other related areas; Have skills in the development and application of machine learning models in supervised and non
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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
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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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, undergraduate and postgraduate education in communications engineering, statistical signal processing, network science, and decentralized machine learning. Welcome to read more about us at: https://liu.se/en
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on futuristic technologies in the field of machine learning and computer vision. Hence, we investigate and develop an innovative computation-in-memory (CIM) solution for artificial intelligence accelerator design