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on fluorescence lifetime imaging (FLIM). Other advanced microscopy techniques such as single-particle tracking may also be applied. The project is to be carried out at the Madrid Institute for Advanced Studies in
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of stable mammalian cell lines, fluorescence microscopy (including live-cell imaging), and genome editing approaches (e.g. CRISPR-based tagging) is advantageous but not required. The role requires flexibility
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or imaging-based methods—such as fluorescence microscopy or other light-based measurement techniques. Familiarity with mouse handling or routine animal work in a research setting, including general care
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, microbial ecology, imaging of biological samples, or other related fields. Candidates should have experience with one or several of the following techniques: fluorescence in situ hybridization (FISH, CARD
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measurements, identification and quantification of microstructural defects by optical confocal microscopy, fluorescence imaging, etc.). The elaboration processes that will be used are based on the formulation
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dissections; tissue fixation and sectioning; immunohistochemical staining and immunofluorescent staining; digital fluorescence microscopy; image analysis using software such as ImageJ, QuPath, and analytical
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field. Experience in the following is essential: single-cell fluorescence microscopy, microfluidics, image analysis, and machine learning (as applied to biological imaging). Python and MATLAB programming
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possess a doctorate in Biophysics, Biochemistry, Molecular Biology or related field. Experience in cell imaging, bacterial and molecular biology, fluorescence labelling, and protein-DNA/RNA interactions is
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molecular biology, fluorescence labelling, and protein-DNA/RNA interactions is essential. Experience in controlling and operating single-molecule/super-resolution microscopes for bacterial imaging, single
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delivery performance and safety. Analytical & Imaging Techniques: Apply quantitative imaging (confocal, MRI, fluorescence), pharmacokinetics, and biodistribution analysis. Data Analysis: Perform statistical