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Field
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to enhance user experience along cycling and walking pathways. Description State of the art and research gaps The accessibility and long-term sustainability of urban environments depend on robust methodologies
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 14 days ago
Perform comparative analyses and ensure interpretability, robustness, and generalization of the models Collaborate with interdisciplinary partners for biological validation and methodological development
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aims to develop a robust multi-robot localization framework for dynamic, unstructured, GPS-denied environments. Your tasks You will conduct high quality PhD research with unique possibilities to perform
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will make water networks robust and resilient to these threats. Candidate requirements Starting October 2026, we require an enthusiastic graduate with a 1st class degree in engineering, maths or a
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distributions and ensure fuel operates within design limits. The aim of this project is to establish a robust, validated framework for neutronics and thermal analysis of prismatic HTGR cores, integrating Monte
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for robust, availability-driven asset management in high-voltage transmission systems. The successful candidate will investigate failure modes, maintenance philosophies, condition-monitoring requirements, and
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research in underwater optical wireless communication (UOWC). Recent studies in controlled in-lab testbeds have shown the possibility of a Gbps data rate. But achieving reliable, robust and resilient data
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profiling and proteomics, to identify key regulatory pathways. A strong translational dimension is embedded in the project. Building on robust preliminary data generated within the host laboratory
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that combine generative AI, reinforcement learning, and human-in-the-loop learning to enable robots to understand tasks at a semantic level and translate them into robust physical actions. You will join the
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. By integrating artificial intelligence (AI), multi-sensor fusion, and cognitive systems, the research will pioneer robust navigation architectures. These improvements are key to making future transport