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) • applicants should hold a master's degree or be in the process of completing it (before September 2024) • proficiency in Natural Language Processing (NLP) and familiarity with Machine Learning (ML) in Python
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phenomenology of land-, sea- and icescapes; and/or (3) remote-sensing-based machine-learning applications for archaeological modeling and survey. Importantly, this work will be carried out in close cooperation
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phenomenology of land-, sea- and icescapes; and/or (3) remote-sensing-based machine-learning applications for archaeological modeling and survey. Importantly, this work will be carried out in close cooperation
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-sectional and longitudinal econometrics and machine learning techniques to determine the relationship between environmental stressors and population health. This project is part of a larger project ECOTIP
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Language Processing (NLP) and familiarity with Machine Learning (ML) in Python • good academic writing skills in English • the willingness to move and reside in the Netherlands. Candidates with the following additional
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vis-à-vis changing environmental/climatic conditions; (2) analysis of viewsheds and the phenomenology of land-, sea- and icescapes; and/or (3) remote-sensing-based machine-learning applications
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PhD position within the research project “Polyglot Machines: Human-like Learning of Morphologically Rich Languages”, financed by a NWO-VIDI Talent Grant and coordinated by Principal Investigator (PI) dr
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different levels of the environmental stress index. In addition, it will employ cross-sectional and longitudinal econometrics and machine learning techniques to determine the relationship between
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Applications are invited for a 4-year salaried PhD position within the research project “Polyglot Machines: Human-like Learning of Morphologically Rich Languages”, financed by a NWO-VIDI Talent
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mindset and aptitude for interdisciplinary research - machine learning skills are mandatory - experience with training and/or designing neural networks for language processing tasks is strongly desired