55 machine-learning-phd-in-denmark PhD positions at University of Groningen in Netherlands
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(e.g. municipality of Groningen and Emmen), etc. This PhD project is one of two positions available within FEBRI that are part of S3ORTED and focus on the business side of this mission. Within
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(e.g. municipality of Groningen and Emmen), etc. This PhD project is one of two positions available within FEBRI that are part of S3ORTED and focus on the business side of this mission. Within
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We are looking for a motivated PhD candidate for a project carried out under the supervision of Prof. Ben Feringa at the Stratingh Institute for Chemistry. The project is part of the EVOLVE
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). The department’s laboratories are well equipped for molecular biology, cell biology, immunology, organoid culture, and omics-based analyses, offering an excellent research environment for a PhD candidate interested
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researcher will receive a tailor-made programme from the GSCF. The PhD candidate is expected to teach a maximum of 350 hours per year The PhD candidate is expected to teach during the first and second year of
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disease, where motor learning is affected at different stages. PhD project Goal: The primary aim of this PhD project is to understand why speech motor skills are disrupted early in Parkinson’s progression
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mechanics at the atomic scale. In this project, the University of Groningen will develop an array of state-of-the-art machine learning potentials for multi-component alloy systems that are relevant
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the PRELIFE program we offer 15 exciting research projects which can be found at http://www.prelife.originscenter.nl of which the research project of the current PhD position is one. This project aims
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We are looking for a PhD candidates for a joint project between the groups of prof. Nathalie Katsonis, prof. Willem Kegel, and prof. Ben Feringa, that will be carried out within the framework
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Organisation Job description This PhD project at GELIFES, the University of Groningen, aims to characterize underwater soundscapes of fish and marine mammals to evaluate impacts of wind farms in