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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 5 hours ago
into specialized evolutionary and local-search algorithms, especially by exploiting parallel and high-performance computing to accelerate the search. Consequently, the internship may involve: reviewing
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 5 hours ago
contribute to the design, development, and experimental validation of novel graybox tunneling algorithms for multi-objective combinatorial optimization, with a particular focus on their parallelization and
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evolutionary and behavioural game theory, multi-agent reinforcement learning, agent-based simulation, or experiments with people and AI systems. Some students may develop new theory or algorithms; others may use
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control platforms, advanced microcontrollers, distributed control algorithms, and artificial intelligence techniques, including neural networks and evolutionary optimisation methods, to enable the efficient
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environments, scripting languages for handling large-scale genomic data, and learning how to apply programming languages to implement complex computational models and algorithms. Learning objectives will include
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control platforms, advanced microcontrollers, distributed control algorithms, and artificial intelligence techniques, including neural networks and evolutionary optimisation methods, to enable the efficient
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methods for additive manufacturing applications, including ANNs and evolutionary genetic algorithms for process optimization supported by programming knowledge (e.g. Matlab, Python). Hands-on experience
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datasets to identify and characterize microbial and plant-derived biosynthetic pathways, predict their ecological functions, and reconstruct the (co-)evolutionary dynamics of traits such as microbiome
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Job Description We are looking for a Research Fellow under the National University of Singapore (NUS) to support a project investigating the fundamental theoretical and algorithmic performance
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to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural problems that also depend