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, implementation and evaluation of BIOMASS Forest Disturbance products Contribute to the algorithm design and testing of new approaches for detecting and quantifying forest disturbances (e.g. deforestation
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teams to contribute to the development of fundamental aspects of computer science (models, languages, methods, algorithms) and to develop synergy between the conceptual, technological and societal
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nonstationary models and algorithms for analyzing various biological signals. The project will focus mainly on developing innovative models for biomedical signals with irregular cyclicity and exploring potential
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analysis, as many observed phenomena cannot be adequately modeled by stationary processes. The NOMOS project aims to develop a new generation of nonstationary models and algorithms for analyzing various
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Title of the project: Genetics of brain diversity in autism The laboratory: Human Genetics and Cognitive Functions Unit (Dir. Thomas Bourgeron) Duration of the contract: 2 years The aim
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evaluation of algorithms for: perception in robotics; sensor based control and navigation ; interactive mobile manipulation; multi-sensor data modelling and fusion. This job offer takes place within
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for: • Contributing to various tasks related to the modeling of lipids and membrane proteins involved in lipid droplet biogenesis. • Developing and implementing the POP-MD algorithm in the OpenMM software
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the necessary data from numerical models and observations to build the dataset; Identify the algorithms best suited to learn the targeted behaviors; Train the learning models; Validate their ability to predict
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components: - operational modal analysis to extract the modes of the probed medium, - algorithmic and experimental developments on the MSE method - and algorithmic and experimental developments on the MFP
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learning, and generative AI Design and implement algorithms for quantum-inspired and quantum-enhanced generative models Investigate theoretical foundations of tensor networks, entanglement, and collapse