Outstanding applicants will join the Broad SV group and focus on the analyses, assembly, and functional prediction of genomic variation from long-ready genome sequencing across multiple research projects and consortia. The team member will focus on leading research projects related to analyses of long-read sequencing and structural variation in population studies such as the All of Us Research Program and the genome aggregation database (gnomAD), as well as rare disease programs including the NHGRI Mendelian genomics program (GREGoR) and the NICHD Fetal Genomics Consortium.
This role will include developing and deploying computational pipelines at scale using methods that will be interoperable across all platforms in the cloud as well as analyzing patterns of structural variation in large and diverse datasets. The role may include deploying existing software and developing novel tools in partnership with our methods development teams as needed, and ideal candidates will be equally adept at both. Exceptional candidates will excel at critical thinking and will be creative, curious, and motivated to develop novel computational methods to solve complex problems. They will have a deep background and track record in data science and programming, with exceptional organization and communication skills. Additional areas of interest could include computational methods for genome assembly, population genetics, functional genomics, or structural variant interpretation in rare disease. The candidate will also receive mentorship and supervision from Dr. Talkowski and a team of experts across the Broad.
- Apply computational methods to discover and analyze structural variation from long-read sequencing of large human genome cohorts.
- Perform quality control assessments with a deep understanding of the data and the underlying biology.
- Develop new computational methods and improve existing methods for genomics analyses.
- Present results to both computational and non-computational audiences, internally and externally, through presentations and/or peer-reviewed publications.
- A track record and/or strong motivation to deeply explore and understand complexities associated with analytical and biological challenges in human genetics and genomics.
- Familiarity with whole genome sequencing and/or transcriptomics data analyses; experience with long-read sequencing data and cloud computing is a plus.
- Excellent oral and written English communication skills are necessary.
- The ability to work independently but within a strong team science culture, and willingness to learn from, train, and mentor individuals with diverse backgrounds and experiences across varied career stages is essential.
- Ph.D., or Masters + 3 years experience, or Bachelor’s + 6 years experience in a computational discipline (e.g. Computational Biology, Bioinformatics, Biostatistics, Bioengineering, Computer Science, Mathematics, Physics, Statistics). Exceptional candidates without these precise credentials will also be considered.
- Proficiency with coding in Python, R, MatLab, Unix/Linux, Java, or C++.
- Proven experience in large-scale data science and/or computational biology.
- Experience with designing computational methods and tools.