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the Luxembourg labour market. A unique urban site with excellent infrastructure A partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and with
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The SiMul team (https://cran-simul.github.io) at the University of Lorraine is offering a fully funded PhD position on the theoretical foundations of self-supervised learning, focusing
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SolideCountryFranceCityVILLENEUVE D ASCQGeofield Contact City VILLENEUVE D ASCQ Website http://uccs.univ-lille1.fr STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo
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. This mainly experimental PhD research project aims to tackle the last scientific obstacles to upscaling by addressing the development of bio-inspired structures capable of controlled tropism compatible with
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existing large datasets with rich information for knowledge synthetisation and triangulation over the course of the PhD project is encouraged. The successful candidate will be affiliated with the Institute
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and educational issues with the common goal of contributing to an inclusive, open and resourceful society. Your role The topic of the PhD will be related to research carried out in our group, focusing
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significant financial support through a government program of "very large research infrastructures" (RI*) of the French Ministry of Science. The APC DUNE group currently has six faculty members and four PhD
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science » Ecology Environmental science » Global change Biological sciences » Zoology Researcher Profile Recognised Researcher (R2) Positions PhD Positions Country France Application Deadline 12 Apr 2025
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, We are seeking candidatures of highly motivated, independent and enthusiastic individuals, with background in cognitive neuroscience and/or neuro-engineering. PhD in neuroscience, psychology, cognitive
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, We are seeking candidatures of highly motivated, independent and enthusiastic individuals, with background in cognitive neuroscience and/or neuro-engineering. PhD in neuroscience, psychology, cognitive