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intelligence, machine learning, data science, applied mathematics, or a closely related field, awarded no more than three years prior to the application deadline*. Documented research experience in machine
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are looking for The following requirements are mandatory: To qualify for the position of postdoc, you must hold a doctoral degree in computer science, artificial intelligence, machine learning, data science
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experiments, and machine learning (ML) to understand and predict multiscale transport phenomena in fuel cell systems. In particular, the postdoc will bridge pore-scale simulations and macroscale performance
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semantic representation models for sign language. Such representations are key to allowing SL to be efficiently processed by large language models (LLMs), and will lead to machine learning models that can
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description and duties The postdoc fellow will conduct research at the borderline between the fields of information visualization / visual analytics as well as machine learning in close collaboration with
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analysis, statistical modelling, linear mixed models, and machine learning among others. The position is well suited for an individual interested in quantitative genetics and data analysis that wishes
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experience with machine learning techniques in general and neural networks in particular will be highly beneficial. About the employment The employment is a temporary position of 2 years according to central
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communication theory, machine learning, complex networks, and optimization. The employment This employment is a temporary contract of two years with the possibility of extension up to a total maximum of three
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be made for special reasons). Experience in research on digital cultures. Proficiency in AI methods (e.g., NLP techniques, machine learning, and large language models, LLMs)—including web scraping
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, e.g., time-series analysis, land use/land cover classification, machine learning methods Experience analysing and visualizing large remote sensing datasets in modern programming language (e.g. R, Python