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English. Demonstrable knowledge of (and interest in) linguistics, language acquisition, cognitive science, or related fields. Demonstrable skills in at least some of the following: computational linguistics
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PhD candidate in the fields of linguistics, computational linguistics, language acquisition, and/or cognitive science. This fully funded position offers the opportunity to conduct cutting-edge research
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/27FCA273D8E512FD1072E06F7DC2D00C and https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4155944 The PhD position is embedded in the research programme Economics, Econometrics and Finance of FEB’s Research Institute. The project
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/(...)?abstract_id=4155944 The PhD position is embedded in the research programme Economics, Econometrics and Finance of FEB’s Research Institute. The project will be supervised by Abe de Jong, in cooperation with Tim
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on various excellence ranking lists. The graduate school of Economics & Business has available: 9 PhD positions in Economics and Business Organisation The aim of our PhD programme is to deliver highly
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PhD positions in Economics and Business (9.0 FTE) (V25.0049) « Back to the overview Job description Since its foundation in 1614, the University of Groningen has enjoyed an international reputation
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for considering components independently. Inspired by so-called contract theories from computer science, such modular control theory will be based on the introduction of assume-guarantee contracts for control
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to the development of a control theory that is inherently modular, i.e., that allows for considering components independently. Inspired by so-called contract theories from computer science, such modular control theory
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theories from computer science, such modular control theory will be based on the introduction of assume-guarantee contracts for control systems. These contracts have two desired features: they should i) be
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, Computer Science and Artificial Intelligence, the PhD student is in charge of data-driven model reduction. This includes three parts: (1) heuristic approaches (symbolic regression), (2) non-intrusive data-driven