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systems capable of selecting and combining models of different complexity, in order to better represent groundwater dynamics and improve large-scale predictions under climate change. Objective — The PhD
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Institut de Recherche pour le Développement (IRD) | Sete, Languedoc Roussillon | France | 6 days ago
scientists, PhD students, postdoctoral researchers, and engineers) in a high-level scientific environment. The objective of this position is to develop and oversee modeling configurations within the ERC
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ICFO is offering a PhD position to a highly motivated student who wishes to start his/her scientific career in a friendly and stimulating environment. The successful candidate will be joining
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. Expected contributions of the Thesis The objectives of the PhD are as follows: To propose a model for representing multimodal data streams, integrating different categories of data (video, metadata, sensors
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which all contribute to the overall goal of understanding social entrepreneurship (SE) scaling. This particular PhD thesis is part of a work package on “Social Business Model Design”. The position is
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contributions & challenges This topic aims to better understand and model the resuspension mechanisms of microparticles exposed to accelerated airflows. It builds upon experimental works conducted during two PhD
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. Funding category: Financement public/privé Région Normandie, financement pas encore confirmé. PHD title: Doctorat de Physique PHD Country: France Where to apply Website https://www.abg.asso.fr/fr
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15 Apr 2026 Job Information Organisation/Company Czech Technical University in Prague Department Department of Control Engineering Research Field Computer science » Modelling tools Researcher
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automata and Zielonka automata, and between the ”standard” projection and the one known as ”Zielonka construction”. This Phd aims to explore new automata models and new projection operators for global types
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, vol. 167, p. 115644, Mar. 2025. https://doi.org/10.1016/j.microrel.2025.115644 [2] A. Bender, “A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions