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Field
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. The objective is to develop models and algorithms that capture spatial variability, uncertainty, and communication constraints, and to understand how these factors influence perception, adaptation, and
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will have the opportunity to develop innovative algorithms and models that integrate multiple data modalities, collaborate with industry partners, and contribute to high-impact publications. Job
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, scalable numerical algorithms for extracting the evolution model of the relevant dynamical skeleton, quantifying associated uncertainties. We will develop mathematical theory underpinning the novel
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typologically diverse languages Creating self-supervised learning algorithms that can assess phonological development and speech complexity in children from birth through age 6, with applications to both typical
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and data processing skills: experience of programming in one or more languages (e.g. R, C/C++, Python, Matlab). Practical experience of algorithm development and implementation of machine learning
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to the construction of the detector at the LNGS. Data taking should start in 2029. The subject of this postdoctoral position, funded by the CNRS for two years, is to prepare the analysis of the first data in order to
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This position focuses on the research and development of novel radiation detectors and associated edge-computing circuits and algorithms for X-ray, particle, and nuclear physics experiments
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structured biological knowledge encoded in genomic graphs. The project will also deliver efficient algorithms to train these models under budget and time constraints, facilitating flexible adoption
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on developing advanced methods for semantic structure extraction, conceptual and argumentative flow reconstruction, rationale-aware content generation, metacognitive prompting, and adaptive personalization. Core
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of computational biology, Genomics, machine learning, and data science, contributing to the development and evaluation of advanced algorithms for analyzing large-scale biological datasets. This role is ideal