43 deep-learning PhD positions at University of Groningen in Netherlands

PhD Machine learning meets choice models (1.0 FTE)

learning meets choice models available. Project description Nonparametric statistical learning provides a flexible and data-driven approach to choice modeling. Recent advancements have improved its economic

PhD Machine learning meets choice models (1.0 FTE)

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

PhD Machine learning meets choice models (1.0 FTE)

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

PhD in Low-Resource Natural Language Processing & Computational Modeling of Language Learning (1.0)

PhD in Low-Resource Natural Language Processing & Computational Modeling of Language Learning (1.0) (V24.0068) « Back to the overview Job description Applications are invited for a 4-year salaried

PhD in Low-Resource Natural Language Processing & Computational Modeling of Language Learning (1.0)

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

PhD in Low-Resource Natural Language Processing & Computational Modeling

Learning of Morphologically Rich Languages”, financed by a NWO-VIDI Talent Grant and coordinated by Principal Investigator (PI) dr. Arianna Bisazza. This is an interdisciplinary project at the intersection

PhD position in Arctic Landscape Archaeology (1.0 FTE)

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

PhD on the Legal Aspects of Indigenous Subsistence Harvesting in the Arctic (1.0 FTE)

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

PhD position on the topic Relational Drivers of Audit Quality: Up Close and Personal

in auditing, governance, and/or behavioral research • a background in (or the motivation to learn) quantitative and/or qualitiative research methods • excellent command of English in speaking and

PhD position on the topic The Relationship between Health and Environment

-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