123 algorithm-development-"Multiple" "NTNU Norwegian University of Science and Technology" Postdoctoral positions in France
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for biomarkers in 7T images. - Development of artificial intelligence algorithms and models for the processing and analysis of MRI images/spectra, focusing on the detection of tumor tissue and the quantification
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Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | 13 days ago
precision and treatment decisions. Within a collaborative project involving researchers, clinicians, and industry partners, the team has developed innovative deep learning–based segmentation methods and built
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 11 days ago
, located at Inria Paris and École Normale Supérieure (ENS). The team conducts research in various aspects of quantum information theory, including quantum error correction, quantum algorithms, and the
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control and energy management strategies, including centralized / distributed control approaches, for ESS coordination and ancillary service delivery. Develop optimization algorithms and Al-based methods
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Alcotra RESIL-AV project, which will start on September 1, 2025, and run for a total duration of three years. The objective of this Franco-Italian project is to develop a common approach to a shared
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des Fluides et d'Acoustique - LMFA) develops a continuum of research in fluid mechanics and acoustics, from the understanding and the modelling of physical phenomena to applied research, in
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repeater based quantum internet. To this end, our overall goal is to develop quantum nanophotonic chips, in which colour centres are used for interference exepriments to mediate entanglement between distant
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reconstruction algorithms. Inconsistencies can be used to correct the input data, for example to improve attenuation correction. The aim of this postdoc is to correct rigid motion in SPECT reconstruction based
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obligations [3]. The tool Verdir ma Flotte (VMF, https://verdirmaflotte.fr/ ), developed by IFPEN with the support of ADEME [4], serves as a decision-support and educational platform. It enables users
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to work with and develop state-of-the-art statistical and mathematical methodology to improve understanding of epidemic dynamics and control. Recruited postdocs will work on one of the new projects starting