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for publishing. Investigates the feasibility of applying a wide variety of scientific principles and theories. Maintains substantial knowledge of state-of-the-art principles and theories. Develops advanced
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is an interdisciplinary project aimed at developing a method for studying shelters with schematic paintings by combining archaeology, geomorphology, materials science, planetary science, cognitive
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/Administrative Internal Number: 495909 Department: Curriculum & Instruction Salary: Commensurate with Experience/Education Description: Possesses, understands, and applies a comprehensive knowledge in area of
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 7 days ago
learning and have strong mathematical skills. Knowledge of bandit models is a plus. LanguagesFRENCHLevelBasic LanguagesENGLISHLevelGood Additional Information Benefits Subsidized meals Partial reimbursement
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with excellent academic record, evidence of practical experience of research in primary school contexts/intervention research and knowledge of reading motivation and/or engagement research. Your
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PhD or be near completion, in physics, mathematics, computer science or a related discipline, and possess sufficient specialist knowledge in the discipline to work within established research programmes
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of probability of statistical machine learning. They will possess sufficient specialist knowledge in network analysis and uncertainty quantification in machine learning and have the ability to manage
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of Education (Ref.: 535006), to commence as soon as possible until 31 August 2026, with the possibility of renewal. Applicants should possess (i) a Master’s degree in Psychology, Neuroscience, Cognitive Science
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) at the University of Luxembourg brings together expertise from the humanities, linguistics, cognitive sciences, social and educational sciences. People from across 20 disciplines are working within the Faculty. Along
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mathematical experts at RICAM with the goal to investigate influence of variable root growth coordinate with UZH and RICAM documentation of data, analysis scripts and model code, and organize knowledge transfer