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fundamental understanding of climate change and its impacts, extending to the development of prototype climate services co-designed by stakeholders and climate modeling experts. The goal is to accelerate
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interactions. PhD topic Within the context of ADVHANDTURE, the goal of the PhD is to design multimodal tactile devices dedicated to the hand for interacting with immersive environments. The main scientific
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process structures. However, this method is limited by the inductive bias of the predefined superstructure. Innovation: Increased computing power and advances in data science have popularized new algorithms
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Arts et Métiers Institute of Technology (ENSAM) | Paris 15, le de France | France | about 1 month ago
, Arts et Métiers and CNAM, dedicated to innovation in the fields of mechanical engineering, materials science and advanced numerical simulation. Located in the heart of the 13th arrondissement of Paris
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(Technology for engagement and personalized support of people with aphasia in rehabilitation). The candidate will join a research team with extensive experience in ergonomics and HCI, particularly in the design
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29 Aug 2025 Job Information Organisation/Company Grenoble INP - Institute of Engineering Department Engineering Research Field Engineering Researcher Profile Other Profession Positions PhD Positions Country France Application Deadline 16 Sep 2025 - 20:00 (Europe/Paris) Type of...
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European project (IsoPROPEL) in close collaboration with Forschungszentrum Jülich (Germany) for cell design and catalytic testing and ITQ Valencia (Spain) for the synthesis of catalysts. The overall goal
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animals. Your Mission You will co-develop a new class of OECT-based battery-free implantable devices that combine: • Wireless analog communication based on backscatter-modulation architecture. • Co-design
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for four years. The project involves multiple partners: • OTFT characterizations : L2n-URCA Reims (O. Simonetti) • Polymer synthesis: ICPEES Strasbourg (N. Leclerc) • Material deposition: ICS Strasbourg (M
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to classical artificial neural networks [8]. Both characteristics – reduction of data and sparse computation – make event-based computing a promising framework for designing and building energy-efficient