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mission, we are in the final stages of developing a prototype for generating daily evapotranspiration products. One of the two selected algorithms, STIC, will be integrated and tested under conditions
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to the causal abstraction research direction, which aims to build rigorous benchmark for evaluating AI interpretability using the framework of causal abstraction and develop new interpretability methods
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 20 days ago
), the objective of this internship is to improve the performance of full waveform inversion (FWI) algorithms for seismic subsurface imaging. This work lies at the interface between Earth sciences, mathematics, and
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of FHE. The project aims to develop more efficient neural network architectures tailored for encrypted computations. The postdoctoral researcher will be supervised by Jean-Christophe Mourrat, in
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of estimation algorithms, use of observers, etc.). • Development of a control architecture integrating data from the localization system. • Experimental validation of the developed system. ADDITIONAL INFORMATIONS
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Arts et Métiers Institute of Technology (ENSAM) | Paris 15, le de France | France | about 1 month ago
can be developed using FPBTs and FBGs coupled with physically informed (PI) machine learning algorithms. SMATSH scientific objectives are then to develop computationally efficient models to predict
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6 Dec 2025 Job Information Organisation/Company CNRS Department Maison de la Simulation Research Field Computer science Mathematics » Algorithms Researcher Profile First Stage Researcher (R1
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26 Nov 2025 Job Information Organisation/Company CNRS Department Institut de Recherche en Informatique de Toulouse Research Field Computer science Mathematics » Algorithms Researcher Profile First
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Is the Job related to staff position within a Research Infrastructure? No Offer Description The researcher will use and further develop ptychography algorithms for transmission electron microscopy data
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(MERCE). The main objective is to develop safe planning and reinforcement learning algorithms with various degrees of confidence for variants of Markov decision processes. More precisely, we will develop