Description & Requirements
Recently, the Somatic Mosaicism across Human Tissues (SMaHT) Network was established by the NIH to catalog somatic genetic variation across human tissues and discover its patterns, causes and consequences. This effort includes all classes of somatic mutation: single nucleotide variants, short insertions and deletions, structural variants and other large chromosomal aberrations. The somatic mutation catalog will enable downstream analyses, such as rates and burdens of mutations across tissues, mutational signature analysis, driver mutations and clonal expansions, and lineage tracing.
The Broad Institute is one of five Genome Characterization Centers (GCCs) within the Network and is tasked with delivering the sequencing data underpinning this somatic mutation catalog. In conjunction with this effort, we are looking for a highly motivated and talented individual with computational background to join these efforts and to lead data curation and analyses for this ambitious 5-year project. Some of our recent work includes Coorens et al., Nature 2021 and GTEx Consortium, Science 2020.
The successful candidate will join an interdisciplinary team working with an unprecedented set of data from a wide range of human tissues and donors, including extensive deep short- and long-read whole-genome sequencing data as well as bulk RNA and duplex sequencing data. The scope of this project provides unique opportunities for developing novel analytical methods for data QC, integration, detection of somatic mutations, multi-tissue analyses, and integration with transcriptomic data.
Overall Responsibility
The computational associate ll will implement, adapt and improve pipelines for data processing, organization, and analysis. This role will require strategic coordination of multiple groups at the Broad Institute (others in the GRO and Cancer Genome Analysis groups) and within the SMaHT Network. In addition, this individual is expected to be able to clearly communicate scientific details and results to other members of the team, as well as other members of the SMaHT Network.
PRINCIPAL DUTIES AND RESPONSIBILITIES
- Apply existing and novel algorithms to genomics data sets, analyze data quality, critically review and analyze results, communicate results to a wide-ranging audience of biologists, computational biologists, software engineers and clinicians.
- Develop data analysis strategies, write algorithms, and deploy computational tools for the exploration of the large data set of the SMaHT Network.
- Explore novel data visualization tools, with emphasis on integrating diverse data types.
- Implement algorithms as software for distribution to the global research community.
REQUIREMENTS
- Bachelor's degree in Computer Science, Computational Biology, Bioinformatics, Engineering, Mathematics, Statistics, Physics, or a related quantitative discipline, with at least 3 years of relevant experience; or a Master's degree in the same field, with at least 1 year of relevant experience.
- Strong programming skills and experience in algorithm development (using Python, Julia, R or another programming language).
- Knowledge of statistics and computational data analysis.
- Knowledge of genetics or biology is a plus.