Bioinformatician II

Mass General Brigham•Boston, MA

1d•Hybrid

About The Position

The candidate will work within 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. As a highly motivated, enthusiastic contributor, will 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. Will process incoming sequencing datasets through established pipelines and will contribute to the development of new analysis workflows. Effectively communicate with other subteams to ensure that new analysis workflows are distributed across teams. Perform high-quality, genome-scale computational analyses under the supervision of the group leader in a timely manner. Quickly learn new analytical approaches and be capable of applying and developing novel computational methods for solving complex problems. Must apply extensive practical programming experience, as well as experience with cloud computation and workflow management systems. Must also contribute 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.

Requirements

Master's Degree Computational Biology preferred or Bachelor's Degree Computational Biology required
Computational Sciences Experience 3-5 years required
Advanced skillset in computational biology, bioinformatics, statistics, or genomics.
Advanced knowledge of statistical association analyses and approaches in genomics studies
Ability to adapt to shifting priorities in response to changing deadlines and the needs of the lab
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.

Nice To Haves

Experience in cloud-based computing preferred
Experience with cloud computing and workflow management systems. Experience with Terra, WDL, and Google Cloud is a plus.
Experience in genomics and handling large-scale datasets is a plus.
Project management skills and/or experience is also a plus.

Responsibilities

Serve as member of the team analyzing the sequencing data for the Autism Sequencing Consortium.
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.
Perform complex data acquisition, storage, cleaning, and pre-processing
Performs advanced quantitative statistical analysis methods
Dissemination of results via presentation and publications.
Process 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.
Perform QC of results and generate 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.
Perform other responsibilities as needed.
Independently design and execute bioinformatics analyses and research projects on
small-mid scale projects.
Develop and optimize data analysis pipelines and workflows.
Collaborate with scientists and researchers to define analysis goals and interpret results.
Analyze data quality and integrity of data output from existing algorithms as part of the complex, multi-step specimen tracking and reporting process, across multiple systems and web-based interfaces.
Develop new and innovative tools to enhance quality assurance review and to improve assay and system performance.
Design and apply novel computational methods/bioinformatics algorithm, machine learning models for building data models and tools using various software and statistical tools to aid in the analysis and interpretation of genetic data, clinical data, images (NGS Algorithm development, Machine Learning).
Analyze large molecular datasets of tumor sequencing data to help critically review and analyze the results of specimen testing, working closely with faculty and staff to troubleshoot problems, recommend technology-based solutions, or determine computational strategies.