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Field
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the mathematical and computational engine of Artificial Intelligence (AI), and therefore it is a fundamental force of technological progress in our increasingly digital, data- and algorithm-driven world
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data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms Assist with organizing large scale multimodal neuroimaging datasets, brain
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algorithms. The candidate should have the following skills: • Strong technical, analytical, and quantitative abilities; • Strong interpersonal, organizational, and communication skills, and the willingness
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microscopy. The ideal candidate will be highly creative, hardworking, and a team player. They will also have the ability to manage multiple projects and students in pursuit of team goals. Representative
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within tissues using our in-house developed spatial transcriptomics-based technology (Spatial VDJ). Using established and newly developed algorithms, we map B cell evolution within tissues, including class
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specific emphasis on the interpretation of single cell results within a biological context. The position also entails close collaborations with multiple groups, many at the Stanley Center in the Broad
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. This work involves developing novel techniques, algorithms, and software packages that enable more robust and scalable approaches to cybersecurity using AI-based techniques. In addition to technical
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, molecular properties, and pathological images. Strong knowledge and experience in data science algorithms, methods, and analysis techniques. Experience in programming using Python and R languages and working
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approaches for important questions in neuroscience. We have multiple current and incoming NIH projects to establish cellular cell type architecture maps of mammalian brains using mice as an animal model. Three
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: Employing satellite observation and machine leaning to improve model representation of ice sheet surface melt”. The candidate will work under the direction of Prof Nowicki and in collaboration with multiple