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algorithms for digital health and AI-driven research projects. Lead technical innovation by exploring and implementing emerging AI methodologies. Support data platform development and retrospective data
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and community engagement. Main objective of the thesis: The PhD aims to develop an eco-flexible, market-aware operational framework for existing HPPs capable of reconciling techno-economic performance
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. Inference methods will be developed within a maximum likelihood framework, based on Newton–Raphson-type optimization algorithms. Particular attention will be paid to the structural constraints imposed by sum
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Infrastructure? No Offer Description The AITAX project aims to address the complexity and dynamics of modern tax regulations by developing a cutting-edge AI solution for automating the analysis and processing
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 1 month ago
preserved at ambient temperature provided it is protected from light and humidity. Goal The goal of the project is to develop an algorithm to allow robust retrieval of data in the context of DNA-based data
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Overview We are seeking an experienced researcher to lead the development of decentralised swarm mapping and localisation algorithms for underground pipe operations as part of an international
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-heuristics, has long favoured the development of algorithms tailored to specific problems, even if based on higher-level search strategies. In combinatorial optimisation, this is justified primarily by
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description languages. Develop and optimize EDA workflows for processor and accelerator design, verification, and physical implementation using open-source tools. Explore architecture-algorithm co-design for
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Offer Description The world is changing at an ever-faster pace. At the Johannes Kepler University Linz, we work on technologies and the ideas of tomorrow on a daily basis. At the same time, we educate
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, operational, and societal constraints. The postdoc will work at the interface of reinforcement learning and computational epidemiology, focusing on the development of new reinforcement learning algorithms