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interpretability and predictive accuracy. We want to explore the structural parameters in choice models (e.g., random coefficient logit models) and obtain valid inferential results using machine learning-enhanced
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well on various excellence ranking lists. FEBRI, the graduate school and research institute of the Faculty of Economics and Business has one PhD position in the field of Machine learning meets choice
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PhD Machine learning meets choice models (1.0 FTE) (V24.0232) « Back to the overview Job description Since its foundation in 1614, the University of Groningen has enjoyed an international reputation
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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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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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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