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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 algorithms for each use case and foundation model. The latter tasks will involve close interaction with the partners responsible for the development of the language models and the partners responsible
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) To develop Deep Learning algorithms to significantly speed up probabilistic inference algorithms of current spatial birth-death models 2) To incorporate fossil stratigraphic and spatial information into a new
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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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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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partners from ICube/Université de Strasbourg, RDP/ENS Lyon, and Inria Grenoble. The overall objective of the 4DPlants project is to develop new methods for the semantic and instance segmentation of time
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existing literature to address this gap. The student tasks will be to prepare the registration documents (e.g., PROSPERO), refine and test the search algorithm in relevant databases, import search results
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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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• Develop, consolidate, and optimize fMRI and EEG neurofeedback algorithms. • Design, integrate, and test standalone neurofeedback software (software suites for clinical environments). • Contribute
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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