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spectrometry imaging data. Conducts git versioning control of R-based lab-wide scripts for basic statistical analysis and preprocessing. Performs statistical analyses on large datasets to provide biological
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imaging data. Conducts git versioning control of R-based lab-wide scripts for basic statistical analysis and preprocessing. Performs statistical analyses on large datasets to provide biological insights
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a related field. No experience required. Preferred Qualifications Prior experience with brain development, and/or cancer cell biology would be an asset. Experience with large-scale genomic data would
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associate to support an ethical, legal, and social implications (ELSI) study aim of the NSF funded study “Integrating Human-Derived Neural Networks and AI for Information Processing in Brain Organoids” under
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genomic analyses on large case-control cohorts to identify risk and response associations for diseases of interest. Performs integrative analyses of other molecular and omics data, such as gene expression
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, GEANT4) will be an advantage. A background in radiation oncology or medical physics will be an advantage. Excellent written and verbal communication skills. Experience with cloud computing and big data
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world leader in genomics. The primary mission of the HGSC is actionable translational research across the full spectrum of human health and disease using large-scale genomic data to drive collaborative
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dynamic and collaborative research environment. Basic data science skills including the statistical analysis of large data sets. Prior experience in one or more of these techniques: design and generation
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skills including the statistical analysis of large data sets. Prior experience in one or more of these techniques: mouse survival surgery, two-photon microscopy and analysis, patch-clamp recording, single
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to promote big tau splice variant and will test these in vivo. Follows up on some of the regulators of tau that we have identified to determine precise site of interaction, and potentially design an assay