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Aix-Marseille University / CNRS | Marseille, Provence Alpes Cote d Azur | France | about 15 hours ago
9 Apr 2026 Job Information Organisation/Company Aix-Marseille University / CNRS Department Mission Europe Research Research Field Biological sciences Chemistry Computer science Cultural studies
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for tomagraphic imaging in tissue Neural network correction of distortions in acoustic transducers web page For further details or alternative project arrangements, please contact: alexis.bishop@monash.edu.
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Infrastructure? No Offer Description At Université Gustave Eiffel (Champs-sur-Marne, Paris region, France), we have an open call for a PhD position titled “Pore Network Modeling of Multiphase Flow in CO₂–Water
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PhD fellowship 2 – Alexander von Humboldt and French-German Networks in the Early History of Ecology
. • Academic transcripts / degree certificates or equivalent For candidates currently enrolled in a Master’s programme (M2) who have not yet defended their thesis but will do so before the start of the PhD: a
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Environments within the general study programme Electrical and Electronic Engineering. The PhD Stipends are open from August 1, 2026, and the integrated PhD stipends are open for appointments from September 1
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into actively morphing and efficient structures? Applications are invited for a 3.5-year UK PhD studentship for the project "Design, Experimental Investigation, Aeroelasticity Modelling and Control of an Aircraft
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universities, research institutions, and museums in a highly collaborative network, supported by the Muoniverse Research School, which coordinates training, exchanges, and career development for PhD students and
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Course: PhD studentship Project title: Exploring a One Welfare approach to human-animal-computer interaction in digital dairy technologies Principal supervisor: Charlotte Doidge Other supervisors
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Description The selected PhD candidate will participate in the EU-funded HORIZON-MSCA-DN-2024-01 project LipAgg. The LipAgg network brings together partners from 6 European countries and comprises 11 academic
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network integration for emerging low-energy opto-electronic AI systems and beyond. The challenge: Machine learning and neural networks are super-charging the complexity of problems that computer algorithms