Computational Scientist I - Genome-scale Computational Analyses

The Talkowski Laboratory in the Center for Genomic Medicine at Massachusetts General Hospital (MGH) and the Stanley Center for Psychiatric Research at the Broad Institute of MIT and Harvard is seeking a highly motivated, enthusiastic candidate to work with our research group to detect, annotate, and characterize genetic variants in large cohorts of patients with autism and other neuropsychiatric conditions. The Talkowski Lab is a large, diverse, and interdisciplinary group of scientists dedicated to the characterization of genomic variation contributing to human disease. The group is leading and contributing to multiple international consortia that collect, process, aggregate, and analyze genomic sequencing data on a large scale.

The advertised position is part of the autism and neuropsychiatric subteam, which is part of the larger variant association team. The candidate will process incoming sequencing datasets through established pipelines and will contribute to the development of new analysis workflows. The candidate is expected to effectively communicate with other subteams to ensure that new analysis workflows are distributed across teams.

We are seeking a candidate to perform high-quality, genome-scale computational analyses under the supervision of the group leader in a timely manner. Successful candidates are expected to be quick learners of new analytical approaches and be capable of applying and developing novel computational methods for solving complex problems. Candidates should therefore have extensive practical programming experience, as well as experience with cloud computation and workflow management systems. The candidate must also have experience with implementing large-scale computational analyses, algorithm development, or statistical analysis. Knowledge of existing analysis tools, methods, and databases in the field of genomics is a significant plus.

This position is hybrid, with the option of flexible remote working hours.

Responsibilities:

• Member of the team analyzing the sequencing data for the Autism Sequencing Consortium. Through this role, you will assist with the development of analysis aiming at (1) calling and annotating variants in short read sequencing data and (2) developing association frameworks to link detected variants to phenotypes.
• Responsible for processing incoming blended genome exome (BGE) datasets (i.e., a cost-effective method that combines low-pass whole genome sequencing with deep exome sequencing from a single DNA sample) from various neuropsychiatric cohorts and calling copy-number variants in these samples.
• Responsible for QCing the results and generating reports to share with collaborators.
• Interact with other subteams, most notably the methods development team, to develop, improve, standardize, optimize, and distribute new and existing methods for genomics analyses to bridge the progress made by different subteams.
• Provide collaborative bioinformatics analysis in support of other research projects.
• Track and communicate progress to internal and external stakeholders at meetings and over Slack.

• Experience with cloud computing and workflow management systems. Experience with Terra, WDL, and Google Cloud is a plus.
• Proficient in Python, R, and Unix/Linux, and/or other scripting languages.
• Proven ability to learn new computational tools and packages.
• Good foundations in statistics.
• Ability to work independently and in a team setting in an organized fashion.
• Good interpersonal and oral/written communication skills in English.
• Strong ability and experience in interpreting computational results and translating these results into biologically relevant conclusions and hypotheses.
• Experience in genomics and handling large-scale datasets is a plus.