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Experience with imaging data processing, anatomical or functional registration, and 3D planning/reconstruction for recording trajectories Required Application Materials: CV One-page statement of interest
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period of 12 months in the first instance, with potential to extend. The project involves advanced theory for new ultrafast imaging experiments and is funded by Engineering and Physical Sciences Research
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to explore the regulation of mRNA modifications in developing cortical neurons. Key techniques will include biochemical approaches, fixed tissue imaging, stereotactic surgery, structural and functional
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related field, and experience in one or more of the following areas: multiphoton imaging, optogenetics, calcium imaging, and / or in vivo electrophysiology. Applicants without prior experience in
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cutting-edge technologies — from single-cell multi-omics and deep learning to live-cell imaging and stem-cell–based organoid systems — to predict, observe, and manipulate epigenetic processes. Our lab and
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deep learning techniques to improve image processing and trait prediction. Analyze large datasets generated by the Phenomobile.v2+ to identify key traits affecting crop performance under stress
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these questions, we use a novel multi-omics approach that integrates high-throughput imaging and machine learning methods with CRISPR/Cas9 screens and saturation mutagenesis to answer central questions about the
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decide the fate of their RNAs - whether to translate, store, or degrade them. Using biochemical reconstitution, fluorescent labeling, and single-molecule imaging, you will explore how molecular machines
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of experimental statistics, signal processing and excellent programming skills (eg Python, R, ...). Previous experience with model-based fMRI experiments, advanced multivariate data analysis and computational
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will develop and exploit mesoscopic, and multiscale computational models to assist medical applications of ultrasound-guided drug and gene delivery and imaging. The project focus are the encapsulated