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. Background in bioluminescence, experimental physiology or cell biology. Experience with 3D morphological reconstruction. Gene manipulation experience (CRISPRcas). Proficiency in English – both written and
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develop skills in AI inference models, data integration, 3D image reconstruction or signal validation experiments. Applications for this vacancy should be made online and you will need to upload a
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will be critical to work closely with the other 3DxN teams, with potential opportunities to utilise and develop skills in AI inference models, data integration, 3D image reconstruction or signal
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of single-cell multi-omics data (scRNA-seq, scATAC-seq, Multiome) to reconstruct gene regulatory networks in 3D forebrain dorsal organoids to determine pathophysiological consequences of aberrant NR2F1 dosage
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-performance computing for one or more of the following: (1) reconstruction of 3D+ structure, heterogeneity, and/or dynamics from scattering and/or microscopy data; (2) autonomous analysis and decision making
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-dimensional reconstruction of various levels of the auditory circuit at the cellular scale. The project's results will thus provide insights into how different aspects of sound are transmitted to the brain with
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of this type of experiment for battery science, as well as for many other research domains. This project will also include the development of iterative reconstruction and noise suppression algorithms towards
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of RNA molecules in gene regulation and human disease. The central goal is to build a predictive framework capable of reconstructing and interpreting RNA-mediated interactions at genome scale by
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-omics data (scRNA-seq, scATAC-seq, Multiome) to reconstruct gene regulatory networks in 3D forebrain dorsal organoids to determine pathophysiological consequences of aberrant NR2F1 dosage Design and build
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, and structural biology. His core scientific research uses computer vision to pioneer new methods for 3D cellular structure analysis and cryo-electron tomography (cryo-ET). Dr. Qirong Ho – Assistant