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on stochastic Riemannian optimization algorithms, these methods still suffer from limitations in computational complexity. The post-doctoral fellow will build upon this preliminary work to investigate
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algorithms for dynamic structured data, with a particular focus on time sequences of graphs, graph signals, and time sequences on groups and manifolds. Special emphasis will be placed on non-parametric
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robots, avatars, social bots, virtual assistants, or AI-driven systems such as chatbots, recommender algorithms, or generative AI. The position focuses on how communicative processes are shaped by and
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observed in Drosophila larvae. This interdisciplinary project combines biology, neuroscience, and computational modelling to understand how the larva’s body’s physical properties influence its motor control
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revisit discretization methodologies in view of modern requirements and computational capabilities. The candidate will focus on developing mesh generation algorithms meeting the following criteria
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) models. Little attention has been paid to other models like graph NNs (GNNs) or PCA. Among the few existing works in the literature, [2] proposes an FL algorithm to compute PCA in a DP fashion, but the
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. The successful candidate will engage with stakeholders from academia, industry, and policymaking to contribute to practical and scalable solutions for global food security challenges. Contact: Prof. Dr. Ralf
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sustainable future. Contact: Prof. Dr. Ralf Seppelt, Director of the Luxembourg Centre for Socio-Environmental Systems (LCSES) Email: Your profile Candidates should have a proven track record in quantitative
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on Neural Information Processing System [20] Anish Agarwal, Munther Dahleh, and Tuhin Sarkar, A marketplace for data: An algorithmic solution, in Proceedings of the 2019 ACM Conference on Economics and
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission