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promise and peril of hybrid intelligence—humans and machines working and learning together. Our mission is to establish an internationally leading interdisciplinary hub that advances foundational research
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ML models and Python programming. Work Objectives: The main objective of this position is to develop, implement, and validate advanced machine learning methodologies within the scope of the project
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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 24 days ago
for automated content generation while maintaining pedagogical constraints, deploy targeted generative guidance aligned with established learning theories, and create compact student models for next-generation
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optimal transport and gradient flows to machine learning and optimization applications, such as deep generative models, sampling, inference, stochastic optimization, and beyond. The doctoral student will
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invites applications for a full-time, Non-Tenure Teaching Track, Assistant Professor position with a specialization in Generative AI, Large Language Models (LLMs), and Deep Learning. We seek a dynamic
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fluorescence microscopy (SMLM, SIM), integrating physical-mathematical models, machine learning, and compressed sensing for accurate and efficient reconstructions. Applicants must submit a project implementing
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machine learning to model network behavior from real-world measurements (e.g., [7]). Although promising, these approaches still face three major limitations: (i) they often rely on idealized and extensive
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related to staff position within a Research Infrastructure? No Offer Description As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have
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including antenna and/or microwave engineering * programming skills and working knowledge of Matlab programming environment * knowledge of mathematical modelling, machine learning and artificial intelligence
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for collaboration. You will also have the opportunity to develop your own research project aligned to the interests of the MND group. This could include new machine learning models or exploring a particular aspect of