Broad Institute

We are looking for an exceptional candidate for a Research Scientist role to join the Diabetes Research Group which spans the Massachusetts General Hospital and the Broad Institute. We are an interdisciplinary team of clinicians, biostatisticians, computational biologists, bioinformatics analysts, software engineers, and laboratory scientists who are working together to investigate the genetic risk factors of type 2 diabetes with an unprecedented set of genetic data linked to clinical data in massive biobanks.

We are looking for an individual who is enthusiastic about taking a hands-on approach to complex problems within a collaborative team of statistical geneticists, computational biologists, and software engineers. Familiarity with genomic data analysis is preferred but not required. The successful candidate will demonstrate innovative and analytical thinking, will have outstanding academic records, an excellent technical background, strong communication skills, and will enjoy working in an interdisciplinary team.

We provide a vibrant research environment with close links to top academic institutions across the Boston area and provides the potential for your contributions to be used and recognized worldwide.

PRINCIPAL DUTIES AND RESPONSIBILITIES:

• Develop, deploy and document cloud-based data analysis pipelines for the analysis and integration of large genetics and biomarker data sets. Support the use of these pipelines by collaborators and other analysts at the Broad Institute.

• Apply cutting-edge computational, mathematical, and statistical methods and algorithms in distributed cloud-computing frameworks.
• Work closely with a multidisciplinary team to analyze large genomic data sets generated by NIH-funded projects.
• Critically review, summarize, and communicate results to researchers and collaborators and contribute to publications.
• Maintain data organization for multiple data sources (including Mass General Brigham Biobank, UK Biobank, and the All of Us cohort)
• Support team members in accessing and analyzing data

SKILLS & COMPETENCIES REQUIRED:

• Experience with coding in standard genomic analysis tools and programming languages (e.g., Python, R)
• Experience with analyzing biological data (including next-generation sequencing data) in a research setting is strongly preferred.
• A background in genetics is preferred. A strong motivation to contribute to the development of tools for genomic research is essential.
• Demonstrated capability as highly organized, a creative problem-solver, detail-oriented, self-motivated, and able to work independently as well as within cross-functional teams.
• Experience with large-scale genetic databases, electronic medical record data, and biobanks strongly preferred.
• Demonstrated ability to proactively remain up-to-date in current statistical genetics techniques and resources, and identify and benchmark novel software solutions against established reference datasets
• Experience working with genotyping and/or gene sequence data – including quality control and association analyses with clinical phenotypes
• Experience with cluster-based or/and cloud computing is required
• Track record of leading and/or contributing to scientific publications is required
• Strong interpersonal, influencing, and collaboration skills to work in a team-oriented, matrix environment, and the ability to work through conflicts
• Outstanding communication, organization, and time management skills

EDUCATION:

• PhD in Biostatistics, Genetic Epidemiology, Statistical Genetics, Computational Biology, Computer Science or related field preferred

EXPERIENCE:

• At least three years of experience working with genetic datasets is preferred – preferably large- scale genetic sequencing data and clinical data – in an academic, pharmaceutical or biotech environment is preferred