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machine learning. The work will be part of a Horizon pilot project aimed at realizing a scenario-based platform for the interactive and comprehensive evaluation of design solutions and mitigation strategies
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learning, chemical intuition, and experimental feedback, you will help reveal the mechanistic origins of high-performance separation membranes and provide design rules for next-generation materials
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description Integreat - the Norwegian Centre for Knowledge-driven Machine Learning at the University of Oslo invites applications for a doctoral research fellowship. The PhD candidate will work at the
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linguistics / sociolinguistics / cultural evolution. Experience in designing and conducting iterated learning, dyadic communication, or artificial language learning experiments. Experience in computational
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Apply now Join our research team as PhD candidate on the DECIDE project, an ambitious inter- and transdisciplinary initiative to design AI systems for decision support, that contribute to the empowerment
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plasticity platform. Different machine learning strategies will be explored to capture the complex relationships between microstructural features and mechanical responses. In particular, the project will
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replication studies in clinical populations using Single-Case Experimental Designs. In doing so, the project integrates tightly controlled experimental paradigms with real-world clinical data, bridging basic
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following: Strong programming skills (preferably in Python), with experience in machine learning/AI or software engineering for interactive systems Desirable experience in game development or design using
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team as PhD candidate on the DECIDE project, an ambitious inter- and transdisciplinary initiative to design AI systems for decision support, that contribute to the empowerment and democratic
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, machine learning, deep learning, high powered computing (requiring Python etc) or a combination of data science and qualitative methods (e.g., interviews and focus groups). Project themes include (but