Job Description:
Job Description The Stevens lab is seeking a dynamic and motivated computational scientist or bioinformatician to join us in the neurobiology division of the Stanley Center for Psychiatric Research at Broad to collaboratively execute and support research in neuroimmunology and the impacts of genetic variation on neurodevelopmental and neurodegenerative diseases. This person will work with our team of neuroscientists and cell biologists as well as with our collaborators in genetics to select methods design experiments and analyze visualize and interpret a variety of genomic transcriptomic and proteomic data.
The Stevens lab and our collaborators generate large quantities of bulk and single-cell RNA and DNA sequencing data from multiple species -- mouse human and non-human primate -- as well as mass spectrometry-based proteomic and metabolomic data. We employ cutting-edge techniques such as Slide-seq -- a spatial transcriptomics method -- and collaborate with those who are creating both the wet-lab protocols and the computational tools needed to integrate data across these modalities. We are seeking a candidate with a strong background in bioinformatics and an interest in supporting multiple projects through the creation and application of analytical tools and end-to-end pipelines. This position offers an excellent opportunity to participate in the Broad Institutes world-class community of computational analysts and jumpstart a career in academia or industry while supporting the core mission of the Stanley Center: to reduce the burden of serious mental illness through research.
What You Will Do: Analyze single-cell and bulk RNA-seq datasets from QC and read mapping to annotation and integration with other datasets. Work with wet lab bench scientists to interpret results of previous experiments and design future experiments. Keep abreast of the latest methods in omics data generation integration and analysis. Communicate progress and discuss ideas with the lab and our collaborators and colleagues.
Requirements Bachelors degree and familiarity with next-generation sequencing analysis principles and methods; or Masters degree in Bioinformatics Data Science or another relevant topic. Demonstrated proficiency in R Python and related languages. Experience with high-performance cluster or cloud computing (Unix/Linux shell scripting Google cloud/AWS).
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