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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 2 months ago
31 Jul 2026 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile First Stage Researcher (R1
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geoscience, energy systems, materials modelling, fluid dynamics, and other scientific and engineering domains where data-driven models must interact with physical knowledge. Such problems raise fundamental
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We offer you We offer a fully funded PhD position in a highly interactive, multidisciplinary, and international research group at the Biozentrum. Our group brings together expertise in molecular
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, AR/VR application development, AI assisted content generation, and human computer interaction in industrial contexts.• Communication: You communicate effectively in English, both orally and in writing
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Per Week 40 Offer Starting Date 1 Oct 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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PhD in Advanced Testing, Modelling, and Simulation of Composite Materials under High Velocity Impact
to join SIMLab at the Department of Structural Engineering, NTNU, in the field of computational mechanics, experimental mechanics, and protective structures. The project focuses on developing next
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8th October 2026 Languages English English English The Department of Computer Science has a vacancy for a PhD Candidate in Empirical Software Engineering Apply for this job See advertisement This is
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Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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Applied Physics, Electrical Engineering, or the equivalent. The PhD position is firmly imbedded in a physics environment, but the candidate strongly interacts with partners in applied physics, applied
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computational approaches to integrate heterogeneous spatial, molecular and imaging data, with the aim of identifying invasion-associated metabolic niches and understanding how tumour–microenvironment interactions