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changes and interaction interfaces. Selected plectin–plecstatin complexes will be further analyzed by cryo-electron microscopy to resolve the structural basis of inhibitor binding and its impact on plectin
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | about 13 hours ago
the outcome of pneumococcal infection. Using an innovative and multidisciplinary approach combining advanced light and electron microscopy, molecular cell biology, proteomics, 3D lung models and in vivo
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, The acquaintance with the spectroscopic methods (UV-VIS, IR, Raman), confocal microscopy, as well as with computer simulation skills is highly desirable. Additional Information Work Location(s) Number of offers
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harmful microorganisms. You will actively work with the characterization of various materials using environmental electron microscopy, X-ray diffraction, AFM, and various spectroscopic methods such as NMR
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of viruses, primarily using electron microscopy, complemented by other methods to understand structure and function. The project involves structural studies of diatom viruses with the aim of increasing
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state-of-the-art magnetic imaging with advanced electron microscopy techniques. You will generate high-quality experimental datasets that form the basis for data-driven micromagnetic modelling developed
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: 2024/55/I/NZ5/03205 Supervisor: Prof. Leonora Bużańska, PhD Supervisor’s email address: buzanska@imdik.pan.pl Project title: The role of aged microglia in exacerbating Parkinson’s disease pathology
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experimental work good written and spoken English motivation for a PhD and ability to work both independently and collaboratively Desirable (nice to have) experience with confocal microscopy, plant
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. The electrodes will be characterized by optical microscopy, scanning electron microscopy (SEM), and X-ray microfluorescence spectrometry (UCCS, Artois) to verify their dimensional and structural quality
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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time