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according to their background and interests. Applicants should have strong quantitative and computational skills (e.g., text or image analysis, natural language processing, large-scale data methods) and a
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samples (subcellular fractionation, striatum slices, dissociated cultures), sorting of biological microparticles by fluorescence, fluorescence imaging and immunoblots, proteomics, analysis and formatting
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slices, dissociated cultures), preparation of vectors for the expression of fluorescent markers, fluorescence imaging and cryo-electron microscopy, analysis and formatting of experimental data, manuscript
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), Biochemistry (production and purification of protein complexes), Structural biology (cryo-electron microscopy and image analysis). The final goal is to build a mechanistic model of substrate recruitment by
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), including: (1) Estimating growth rates from image analysis by comparison with in situ reference samples; (2) Developing a growth model as a function of environmental parameters (e.g., temperature, depth); (3
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closely with our collaborators to establish a deep learning-based image analysis pipeline. The successful applicant should hold a PhD in cell biology or neuroscience. Previous experience in live cell
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environment, with access to state-of-the art brain imaging facilities (two research-dedicated MRI scanners / 1.5 and 3T, hybrid PET-3T MRI, MEG-EEG). The vibrant research community at CRNL and other nearby
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equipment, particularly in imaging and electron microscopy, image analysis, and bioinformatics. The team is composed of five people. The thesis will be carried out as part of a collaborative ANR project
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. - Have skills in image analysis (segmentation, cell tracking, spatio-temporal quantification) and quantitative analysis of biological data. - Familiarity with classical approaches in protein biochemistry
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using the KM3NeT detectors • Data analysis from SVOM instruments as well as images from the COLIBRI telescope • Participation in KM3NeT shifts and service tasks (calibration, construction, processing), as