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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
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mathematics, (theoretical) computer science, machine learning foundations, electrical engineering, information theory, cryptography, statistics or a related field. - Advanced knowledge of probability theory
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emphasis is placed on building information modelling, point cloud capturing and processing as well as knowledge representation and inference. In the research project AI-CHECK, new technologies for checking
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-to-store-human-knowledge-for-eternity We are looking for a student with a strong mathematical and/or coding background. Interest of background in coding theory, information theory, and algorithms is desired
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knowledge and practical experience with Software Engineering in general and your desired field of specialization in particular Motivation to build innovative solutions involving industrial partners Strong
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, Computational Linguistics, Data Science or a similar field Good theoretical knowledge and practical experience with Natural Language Processing (rule-based and/or machine learning) Software Engineering Motivation
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master’s degree in Computer Science, Geodesy, or related discipline Very good programming knowledge, preferably in Python Experience with state-of-the-art machine learning or data science technologies
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good programming knowledge, preferably in Python Experience with state-of-the-art machine learning or data science technologies Experience with remote sensing data is a plus Experience with industry
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and its epistemic effects in forest research” seeks to enhance the understanding of how dimensions of inequality in academia intersect and impact on knowledge production, using forest science as an