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Field
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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
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participation of citizens. You will focus on developing adaptive learning systems that enhance the transparency and contestability of AI decisions through personalized, multimodal explanations. Your job AI is
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 23 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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telecommunications networks and urban infrastructures Change: Developing data analysis and modelling methods to understand the interdependency Impact: Better design to enhance telecom and urban performance Job
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strategies (e.g., feature attribution, counterfactual explanations, dialogue-based explanations, hybrid symbolic–ML approaches); develop user-facing explanation interfaces that connect algorithmic reasoning
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, to create a unified and reliable representation of structural integrity. The work expands on TU/e’s contributions by developing algorithmic components for detection and classification of defects and anomalies
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Technology Centre (MTC). You will push the limits of multiphysics CFD for laser manufacturing by developing a next-generation simulation capability for laser drilling - with relevance to additive
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and limited resources (fleet size, mobile and fixed charging infrastructure). This project aims to address these challenges by developing novel mathematical models and algorithms to support real-time
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Program for Data-Driven Life Science (DDLS) aims to recruit and train the next generation of data-driven life scientists and to create globally leading computational and data science capabilities in Sweden
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling