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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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Python-based frameworks or a web application) enabling image upload, AI-based analysis, and visualization of bacterial phenotypes. Perform image analysis using existing deep learning algorithms developed
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Inria, the French national research institute for the digital sciences | Bron, Rhone Alpes | France | 26 days ago
unified understanding of behavioral adaptation. The project aims to: Develop and analyze computational models that capture flexible, multi-timescale learning and adaptation in recurrent neural circuits
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a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The position aims at developing experiments using spin qubits in arrays of semiconductor
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18 Nov 2025 Job Information Organisation/Company CNRS Department VERIMAG Research Field Computer science Mathematics » Algorithms Researcher Profile First Stage Researcher (R1) Country France
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Description Evaluation of the robustness of ML algorithms executed on a non-hardened accelerator through circuit-level fault-injection The project addresses the challenges of deploying AI applications
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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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economy environments, intermediate systems have been developed to facilitate the processes of recovery, reuse, and recycling. However, in terms of energy systems, the processes of reuse, recovery, and
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safety-critical tasks, such as healthcare or automated vehicles, where trustworthy models are required. The existing literature for the OoD detection problem focuses on the development of confidence scores
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involves developing state-of-the-art methods for image segmentation, detection, classification, predictive modelling, and image enhancement. We aim to build more trustworthy and robust AI models that can