The Allen Institute for Brain Science, located in Seattle, Washington, is comprised of a multidisciplinary staff committed to understanding how the brain works and helping to unlock the mysteries of neurological diseases and disorders affecting millions worldwide. Serving the scientific community is at the center of our mission to accelerate progress toward understanding the brain and neurological systems. The Institute is embarked on a 10-year mission to discovery underlying principles of cortical organization, circuitry and function. A key part of that mission is to advance our understanding of detailed cortical circuitry by characterizing and classifying the cell type components that comprise the building blocks of these circuits in both mouse and human cortex.
This candidate will work in a collaborative setting, providing data analysis support for transcriptomic and epigenetic efforts to classify and characterize human cortical cell types. Projects involve the use and development of computational tools for analyzing high-throughput single cell/nucleus transcriptomics data sets, and for analysis of ATAC-Seq and other epigenetic data to support the development of cell-type-specific reporter tools for mouse and humans. Candidate backgrounds can span bioinformatics, physics, neurobiology, or computer science, ideally with a multidisciplinary computational and biological focus.
- Use and improve an existing pipeline for analysis and visualization of population and single cell ATAC-Seq dataset.
- Define cis-regulatory elements from epigenetic data, and external data sets to be used in functional testing.
- Maintain existing tools for visualization and analysis of single nucleus/cell RNA-Seq data
- Compare newly-generated single nucleus/cell RNA-Seq data with existing reference data sets for quality control and scientific purposes
- Design analyses to address predefined scientific questions in single nucleus/cell RNA-Seq data (e.g, measuring alternative splicing between cell types)
- Maintain clear and accurate communication with supervisor and team members
- Bachelor’s or advanced degree in life sciences, physics, math, engineering, or computer science.
- Experience with computational analysis of biological data sets
- Specific experience in analysis of ATAC-Seq, RNA-Seq, and/or related data
- Expertise in at least one programming language (preferably R)
- Familiarity with additional programming languages (e.g., python, perl, C/C++).
- Expertise with the Linux systems
- Strong written and verbal communication skills
- Ability to work independently and collaboratively.