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Field
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imaging tools. Our goal is to understand how specific RNA molecules are spatially and temporally organized within cells to regulate eukaryotic gene expression and cellular function. This research is based
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chemical and genetic perturbation tools coupled with high content imaging and single cell -omics to screen for regulators of disease states in complex in vitro human models Decode biological insights from
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. fluorescence imaging, molecular biology, cell culture, immunohistochemical assays, circuit manipulations, mouse surgery or behavioral assays) and electrophysiological recording (in vivo extracellular recordings
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strategies that modulate the crosstalk between tumor and immune cells, and develop new image-based screening technologies to identify targets that mediate clinically-relevant cell-cell interactions
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following topics and tasks: Machine learning/Artificial Intelligence methods for automatic interpretation/classification of the RIMFAX radar images. Retrieval of geophysical parameters, such as dielectric
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modifiers. The cultures will be analysed using basic molecular and cell biological techniqu es as well as high throughput imaging and analysis to observe modifier effects on LRRK2 and LRRK2 Rab substrate
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Biology, Systems Biology, Neuroscience, Immunology or a related field. Expertise in tool development including any of the following areas: spatial omics, advanced microscopy, label-free imaging, genetic
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, re-apply if you significantly improve crucial aspects of the rejected application. The selection procedure Icon Applicants Applicants Icon Foundation Foundation Icon Notification Notification
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in NLP. Completed a PhD or equivalent qualification or research experience in machine learning, natural language processing and image processing. Emerging track record and recognition for quality
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The Computer Vision-Core Artificial Intelligence Research (Vision-CAIR ) group led by Prof. Mohamed Elhoseiny at the CS Program of the King Abdullah University of Science and Technology (KAUST) is