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Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | 6 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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and localization of a potential fault using the Matched Field Processing (MFP) method, based on the reconstruction of a response model of the inspected structure from the modal parameters predicted by
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biology OR virology A solid background in virology, transcriptomics and imaging Hands-on experience with experimental animal and/or iPSCs models Technical expertise in working in BSL-3 environment A
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coordinated by Prof. Isabelle Boutron (Université Paris Cité – Inserm, CRESS). Background : Evidence-based clinical practice guidelines (CPGs) are essential tools in patient care, yet only 10 to 20
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their metabolic activities to understand their role in carbonate precipitation. The objectives of this work will be to: Map the New Caledonian lagoon and quantify the precipitated carbonate sludge. Model
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Postdoctoral position: Developing a human lymphoid organ-on-chip to evaluate candidate mRNA vaccines
. To address this issue, we developed a lymphoid organ-on-chip (LO chip) model based on a microfluidic chip seeded with human PBMC at high density within a 3D matrix. Perfusion of the SARS-CoV-2 Spike
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-analysis and modelling are particularly encouraged to apply. Where to apply E-mail marcello.solinas@univ-poitiers.fr Requirements Research FieldNeurosciencesEducation LevelPhD or equivalent Research
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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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. However, while the effects of high doses of IR are well understood in a variety of models, including colon cancer [1], a wide variety of issues and questions remain concerning low dose effects, for which
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and physics, Materials Mechanics, Geotechnics, and Civil Engineering Proven skills in laboratory and/or field experimentation Potential aptitude in numerical modeling Ability to work in a team and in