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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The objective of this postdoctoral position, in
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experiments. The objective is to develop Bayesian causal models and neural networks capable of identifying relevant causal relationships between instrumental parameters and observed anomalies. The work will
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maximum likelihood and Bayesian inference frameworks. - Data mining in genome databases. - Large-scale phylogeny reconstruction (archaea, bacteria, and eukaryotes). - Implementation of complex sequence
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experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
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links) and Space Domain Awareness (tracking satellites, debris, and near-Earth objects). Expanding AO to these domains introduces challenges: extreme performance for faint or high-contrast targets
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there. USM makes it possible to replace traditional heuristics with AI-based techniques for memory management. The objective of this project is to explore the use of AI within USM and to investigate
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for the automatic characterization of roadside edges. Roadside objects can be small (grass strips) and/or three-dimensional (ditches, hedges) and extend over large areas (landscape scale). The post-doc will be
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. The institute brings together 15,000 researchers, engineers, technicians and administrative staff, with a common objective: to improve the health of all through progress in knowledge of living organisms and
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will involve the production, purification, and characterization of the receptors of interest, in the presence or absence of their effectors (G protein, β-arrestin). The objective is to determine the
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data to refine objective measures of neural function and improve clinical strategies for hearing aid optimization in this population. References: [1] A. Starr, T. W. Picton, Y. Sininger, L. J. Hood, and