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Field
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research project on the optimal energy storage control under distribution system constraints. You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and
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you co-design solutions that will enable the development and operation of new algorithms and software to solve leading-edge research problems. Want to help build, maintain and secure some of the largest
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these services. You will design and debug platforms, and will work closely with researchers as you co-design solutions that will enable the development and operation of new algorithms and software to solve leading
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will work closely with interdisciplinary researchers and engineers to develop novel AI algorithms, publish in top-tier venues, and translate research innovations into real-world sustainability solutions
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implementation novel machine learning and large language model (LLM) algorithms for Green AI applications. Support the research of efficient AI techniques, including model optimization, parameter-efficient fine
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protection of complex, non-transportation interdependent civil infrastructure networks. We seek candidates with particular interests in water distribution systems and networks. Core Responsibilities The
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. The role spans the entire research pipeline – from processing spatio-spectral-temporal UAV imagery to model development, algorithm validation and deployment, including contributions to a QGIS forest
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systems. Specifically, the research will propose an integrated framework that will couple two core components: 1) advanced algorithms to optimise participation of HPPs, or more generally of VPPs integrating
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 2 months ago
://jobs.inria.fr/public/classic/en/offres/2026-10317 Requirements Skills/Qualifications Technical skills and level required : a strong understanding of distributed algorithms software design and development skills
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follow specialized training programs (e.g. ARENA). Specific Requirements Knowledge: Linear algebra, probability and statistics. Graph theory and algorithms on graphs. Machine learning and deep learning