We are seeking a motivated Associate Computational Biologist (ACB) to join the Sheng Lab at the Broad Institute of MIT and Harvard. We are a team of scientists studying the genetic basis and molecular mechanisms underlying schizophrenia and other brain disorders. This candidate will collaborate with biologists and geneticists to perform various analysis including transcriptomics and proteomics analysis, pathway analysis and biological interpretations.
This position in the Stanley Center for Psychiatric Research involves computational analysis of bulk and single-nucleus RNA-Seq. This person will apply existing computational methods, and interpret results within a biological context. This researcher will work in close collaboration with laboratory scientists on analysis of a range of projects with a strong emphasis on bulkRNAseq and single cell approaches. The scope will include integration with other internal and external genomics datasets. The role will often involve rapid prototyping in support of a dynamic, fast-moving experimental program; it is focused on molecular biology applications relevant to investigation of brain function and psychiatric illness. The position will provide an opportunity to become a part of the computational biology community at the Broad Institute.
● Analyze large RNA-Seq datasets to profile transcriptomes from different brain regions at different ages, and interpret results to derive important biological insights into these models.
● Work with wet-lab biologists to design and implement appropriate experiments for future computational analysis.
● Work with other Broad computational biologists experienced with RNA-Seq, including those in the Levin group to learn, discuss, and integrate the most appropriate solution for an experiment or project.
● BS.C. degree with experience in working with RNAseq data or MS.C. degree in Bioinformatics, Computer Science, or other relevant scientific discipline or equivalent experience is required.
● Should have a demonstrated proficiency in R and/or Python, or related languages
● Experience with and solid understanding of statistical analysis is required
● Familiarity with next-generation sequence data analysis tools, particularly those for RNA-seq
● Understanding of molecular biology and next generation sequencing is highly preferred
● Familiarity with single cell data analysis is preferred.
● Familiarity with working on a computing cluster/server (important skills: Unix/Linux, shell scripting)