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Are you passionate about pushing the frontier of catalysis science? The Center for Visualizing Catalytic Processes (VISION) at the Technical University of Denmark (DTU) is offering mutiple Postdoc
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be used to prepare lamella samples for high resolution cryo-EM imaging and tomography. From AI assisted image analysis, 3D models for key proteins and biomolecular complexes will be fitted into 3D
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Postdoc opportunity within single molecule fluorescence imaging funded by Villum fonden. We seek a postdoc candidate with experience in experimental biophysics to join the single molecule biophysics
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an expert in the extracellular vesicle field with skills in genetic engineering of extracellular vesicles (including transient/stable transgenesis of zebrafish), live embryo imaging, and spatial
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DTU Tenure Track Researcher on Nanoreactors for Operando Visualizations of Nanoparticle Catalysis...
microscopy for nanoparticle catalysis at the Center for Visualizing Catalytic Processes (VISION). Responsibilities and qualifications You will engage with VISION’s development and application of nanoreactors
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. Nature Physics20, 970 (2024)). You will also work on expanding our coherent imaging methodology to look at dynamics and phase switching in materials at the nanoscale (Johnson et al. Nature Physics19, 215
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cellular processes efficiently. This project aims at understanding the formation and functioning of aggregate-forming Archaea-Bacteria partnerships. The project involves working with syntrophic deep-sea
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an experience in technology-assisted monitoring or computational image analysis. Expected start date and duration of employment The position will start in June 2026, with exact starting date as agreed between
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functional properties. The post doc position is part of the Food technology group at Department of Food Science, Aarhus University and may also include teaching and dissemination activities, as
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
hybrid models that integrate limnological knowledge into machine learning models following the paradigm of Knowledge-Guided Machine Learning (KGML). The position is part of an on-going project