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Field
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PhD Position - Marie Curie network ON-Tract: Protein engineering of enzymes: in vitro directed evolution and machine learning-based elaboration of biocatalysis for synthesis. A doctoral position is
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pooling coordination schemes for CF-based 6G RANs. His/Her work will adress objectives like: (i) develop low-complexity ML algorithms for efficient multi-objective network optimization, radio resources
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-loss events undermine statistical confidence. The aim is to develop i) edge intelligence (on-turbine smart algorithms for data preprocessing), ii) resilient data movement (error-tolerant, cybersecure
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the development of methods and models refinements, analyses, and optimizations for scale-grid TES integration and operation planning algorithm. RESTORATIVE consists of 17 PhD students at 7 universities and 4
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 8 days ago
to advancing algorithms for human-centered robots: robots that are not working autonomously in isolation, but that instead react, interact, collaborate, and assist humans. To do so, these robots need
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environment who will supervise the PhD and collaborating with the rest of the Doctoral Network fellows. Where to apply Website https://cv.newton-6g.eu/ Requirements Research FieldEngineering » Electrical
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of dynamic outdoor thermal comfort. This objective aims to reduce the computational demands of microclimate simulations and thermal comfort analyses by developing fast parametric algorithms and data-driven
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. Lab Research: • AI-Driven Algorithms & Software: Develop deep leering/machine learning/statistical based algorithms to elucidate lncRNAs, fusion transcripts, RNA modifications, and circular RNAs in
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, abandonment, comments, peer interaction) Formalization of algorithms for orchestrating educational AI agents : Train RL and LLM agents and study multi-objective optimization (mastery, well-being stability) Work
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will focus on developing theoretical and algorithmic foundations for goal-oriented, semantics-aware communication enabling timely and reliable cloud-to-agent interactions. For more details on semantic