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Field
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to reconstruct subsurface defects; Implement image/signal‑processing or machine‑learning pipelines for automated flaw characterisation; Collaborate with the Federal University of Rio de Janeiro, including short
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hands-on experience in tissue handling, histology, microscopy, and spatial transcriptomics. Experience with the computational analysis of NGS- or imaging-based spatial transcriptomics and single-cell
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and/or image processing * Strong proficiency in programming with Python and Matlab * Good command of English Knowledge of solid mechanics would be an asset, but is not essential. Website for additional
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | about 2 months ago
vivo models of PD Apply and further develop methodologies such as disease modeling, virus-mediated gene delivery, behavior, immunohistochemistry, tissue clearing and 3D imaging, image analysis, spatial
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transfer. We use complementary approaches including cryo-EM, biophysical methods and in vivo functional assays to study the protein machineries involved in this process. Join our young, ambitious, and
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Employment 1.0 FTE Gross monthly salary € 3,546 - € 5,538 Required background PhD Organizational unit Faculty of Science Application deadline 09 November 2025 Apply now The goal of the project is to
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correlations, probabilistic evaluation, scalability). Prototype and evaluate data system components or extensions to existing open-source engines. Publish in top-tier conferences (SIGMOD, VLDB, PODS, ICDE, ICDT
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of what criteria will be assessed at each stage of the recruitment process. * Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs
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responsibilities will be to: Photonic System Innovation: Craft state-of-the-art instruments and components for commercialisation across optical communications, hyperspectral imaging, and astronomical applications
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initiation, progression, therapy response and prognosis, and (iv) novel microbe discovery in cancer and other chronic diseases. The knowledge gained using our “tumor ecology” paradigm will be translated