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, fluorescence lifetime and vibrational imaging methods. Large-scale and high-throughput imaging and analysis pipelines: data acquisition and analysis to characterize cell-types and connectivity in mammalian brain
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Qualifications PhD in Neuroscience or other related field Experience in in vivo dosing (IV,IP, SC), mouse brain stereotactic surgery, in vivo two photon imaging, image analysis Qualified applicants must be
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physiology Competency in scientific programming (e.g. ImageJ, Python) for data analysis and image processing. About the Lab & Environment. The Krishnakumar lab is a highly collaborative group with access
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of food ingredients. The research is focused on structural and physical aspects of food ingredients and food matrices using high resolution microscopy and image analysis. We are seeking a highly motivated
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, a novel spatial discovery proteomics concept that integrates microscopic cell phenotyping with deep-learning based image analysis and global MS-based proteomics. This unique method was recently
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models, for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics), large textual corpora (e.g., scientific literature), and/or pathologic images. Our research
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), combining state-of-the-art in vivo approaches with quantitative data analysis. About the lab and environment The Rebola Lab (https://therebolalab.org ) studies how variability in synaptic function across
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human health. Within this mission, the Jug Group develops advanced computational methods and open scientific software to extract knowledge from complex biological imaging data. We work at the intersection
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including CyTEK, Multiplex imaging and Single-cell Seq and proteomics, etc. The successful applicants should have a proven academic publication track record, including first-authored publications at high
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(STED) and Stochastic Optical Reconstruction Microscopy (STORM) Cryo-electron tomography Imaging data science and AI-based analysis A strong record of contributions to peer-reviewed research publications