Computational Scientist I- Center for Genomic Medicine

The Talkowski Laboratory in the Center for Genomic Medicine at Massachusetts General Hospital (MGH) and the Broad Institute of MIT and Harvard is seeking a highly motivated, enthusiastic Computational Scientist to work with and support our research group in analyzing sequencing data to identify structural variants within the human genome using genomic population databases and aggregating phenotype and genotype datasets.

We are comprised of an interdisciplinary group of scientists, technicians, bioinformaticians, computational biologists, and postdoctoral fellows who work together in a mutually supportive and respectful environment. Ideas are freely shared, and contributions are highly valued. We are dedicated to characterizing genomic variation contributing to human disease, with a focus on the relationship between genome structure and function. The lab integrates molecular and computational genomics methods to investigate the genetic architecture of neuropsychiatric disorders and develop new technologies for translational applications in genetic diagnostics. The lab has served as a hub for novel gene and variant discovery and functional genomics modeling in common complex and rare Mendelian disorders.

At a minimum, candidates should have a PhD in genetics or a related field. Additional postdoctoral experience is preferred, but not required. Candidates should have a deep computational background, including experience in statistical genetics, programming languages, and data science. They should excel at critical thinking, performing large-scale analyses, and demonstrate an ability to learn, develop, and apply new computational tools and methods. They will seek to understand which models and tools would drive progress on core scientific questions, lead the effort to develop and apply them, and collaborate on publishing and presenting the work. Knowledge of existing bioinformatics analysis tools, methods, and databases is a significant plus.

Candidates will have the opportunity to work in a unique translational genomics environment within the CGM, which seeks to integrate computational genomics, technology development, and molecular genomics methods. The MGH and the Broad Institute provide a vibrant research environment with close links to top academic institutions across the Boston area, and provide the potential for your contributions to be used and recognized worldwide.

This position is hybrid, and candidates can work remotely as needed

Education requirements: A PhD degree in a quantitative discipline (such as computational biology, biostatistics, statistical genetics, computer science, bioinformatics, or in biology with a strong quantitative background). Additional postdoctoral experience is preferred.

Minimum years of experience: 2+ years of direct work experience.

Responsibilities of the role:

• Perform large-scale data analysis on genomics data and bulk sequencing data for collaborators
• Mining of genetic databases and resources to evaluate loci for gene discovery
• Conceive, implement and test genomics models; work with wet-lab researchers to translate these models into testable experiments; help analyze data from experiments
• Evaluate and recommend new emerging data analysis tools
• Create scientifically rigorous visualizations, communications, and presentations of results
• Contribute to the generation of pipelines, protocols, publications, and intellectual property

Minimum requirements: 

• Experience with biological datasets, preferably large-scale genotyping and/or sequencing data.
• Proficiency in at least one modern programming language. Experience with a scientific programming environment, such as R or Python, is preferred.
• Experience in cloud-based computing preferred, but not required.
• Familiarity with next-generation sequence data analysis tools; ideally will have some prior experience with statistical methods, pipelines and tools relevant to genomic data analysis.
• Experience with publicly available genetic databases (eg GTEx, Roadmap, gnomAD, UCSC, GWAS catalog) preferred.
• Independent, highly motivated, and highly collaborative with the ability to work together with multi-disciplinary teams of biologists, laboratory scientists, bioinformaticians, and physicians.
• Strong communication skills.