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non-relativistic holographic frameworks. The project focuses on establishing and using controllable limits of string theory and holography—particularly non-Lorentzian (e.g. Galilean/Newton–Cartan and
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., probability, analysis), eager to conduct cutting edge research in the field of uncertainty quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves
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formal language theory Computational models of language acquisition, especially building models for phonological and syntactic learning Mechanistic interpretability and controlled evaluation of language
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applications (https://dcm.univ-grenoble-alpes.fr/research/ingenierie-et-interactions-… ). The candidate will be based Grenoble, with secondments in other laboratories of the network. Grenoble is the largest city
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join a high-impact research team advancing the theory and application of learning, control and optimisation in multiagent and complex networked systems. This is an exciting opportunity for an early
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motivated Research Fellow to join a high-impact research team advancing the theory and application of learning, control and optimisation in multiagent and complex networked systems. This is an exciting
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motivated Research Fellow to join a high-impact research team advancing the theory and application of learning, control and optimisation in multiagent and complex networked systems. This is an exciting
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quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves getting Bayesian type uncertainty for parameters given data (i.e., a posterior type distribution
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Position Type: Postdoctoral Fellowship Duration: 2 years Start Date: 1 September 2026 Area of Specialization (AOS): Philosophy of Cognitive Science; Cognitive science; Cognitive control Area of Competence
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control theory Help mentor graduate and undergraduate students Participate in other ongoing research activities within the areas of connected and automated vehicles and intelligent transportation systems