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Field
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-atmosphere version of the general circulation model ICON, i.e. UA-ICON, a state-of-the-art high-resolution model of the neutral atmosphere with a model top at 250 km height. UA-ICON includes a deep- atmosphere
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learning, computational mathematics, and probabilistic modeling, with direct applications in medical imaging and beyond. Details can be found in the link below. The position is suitable for disabled persons
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functionality and analyzing integrated safety mechanisms result in high simulation times. To better address these issues, a virtual prototype will be created. This prototype will significantly reduce simulation
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The Department Signatorics at the Fraunhofer Institute for Optronics, System Technologies and Image Exploitation (IOSB) in Ettlingen is offering a full-time position on the subject of adaptive
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context, we developed label-free NAD(P)H fluorescence lifetime imaging (FLIM). We previously found (i) that during the life cycle of helminths, i.e., H. bakeri in mice, both bioenergetic and defense
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Max Planck Institute for Medical Research, Heidelberg | Heidelberg, Baden W rttemberg | Germany | 28 days ago
Master’s degree in Physics, Biophysics or similar. Ability to work independently and within a team. Attention to detail and high level of critical thinking. Experience with photonics, fluorescence, imaging
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, biomechanics, single cell-analyses, advanced imaging, and animal models. Tasks: to actively pursue the proposed project with the aim of characterizing the molecular, biomechanical and functional mechanisms
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basic and multiomics data analysis, Flow cytometric analysis of immune cell populations Immunohistological staining and imaging Biochemical assays for cytokines and other inflammatory mediators Protein
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-weighted imaging, and EEG, in combination with genetic data (GWAS, bioinformatics) from large-scale population cohorts. Positioned at the intersection of biological psychology, cognitive neuroscience, and
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applications. Our overarching aim is to obtain a holistic view of interconnected biological systems in health and disease. We develop clearing technologies for cellular-level imaging and deep learning algorithms