Computational Scientist I

The Broad Institute•Cambridge, MA

22h•$88,000 - $124,000•Onsite

About The Position

The Broad Institute of MIT & Harvard is seeking a highly motivated Computational Scientist to join the Xavier Lab to lead and direct data generation and analysis projects designed to determine the underlying factors contributing to health and disease. We are an interdisciplinary group with expertise in computational analysis, genomics, microbiology, and immunology. The candidate for this position will be working closely with computational and experimental biologists, including graduate students, post docs and staff scientists in the group. They will contribute by directing, planning, and executing the analyses of large multi-omic datasets with the goal of identifying biological features (e.g., genes, microbes, variants) that are relevant to human health. Prospective applicants should have made significant contributions to their area of study, as evidenced by a strong publication record. We are seeking creative and highly motivated individuals who want to work in a dynamic, multi- disciplinary research environment.

Requirements

Ph.D. in Computational Biology, Computer Science, Physics, Math, Statistics, or related quantitative fields.
4 to 5 years of experience working on projects utilizing bioinformatics, data analysis and statistics.
Excellent critical thinking, research, and analytical skills.
Excellent communication and interpersonal skills and the ability to work with biologists, computational biologists, data scientists, and software engineers.
Must be able to work independently as well as part of a team in a fast-paced, highly collaborative environment.
Must have experience that demonstrates the ability to carry out a variety of tasks in parallel, recognize and solve problems effectively, and shift priorities rapidly.
Scientific and numerical programming in Python or R and knowledge of Machine Learning methods.
Well versed in Next Generation Sequencing pipelines (single-cell RNA-Seq, single-cell ATAC-Seq, etc.).

Responsibilities

Oversee data generation and data analysis across various internal and external collaborations. Includes working datasets such as single-cell RNA-Seq, single-cell ATAC-Seq, spatial transcriptomics, proteomics, metabolomics, and/or microbiome data.
Demonstrate flexibility to execute tasks requiring various skill levels and learn new skills as needed.
Perform analyses using current processes and identify, propose, and implement improvements to ensure output of high-quality datasets.
Work with other team members and leadership to plan project requirements and timelines, shift priorities as needed, and efficiently execute project tasks.
Identify and help solve methodological problems, including adjustments to experimental and computational protocols to ensure generation of high-quality datasets suited to answer core biological questions.
Use single cell and spatial transcriptomic approaches to understand tissue organization and how they are altered in disease environments such as chronic inflammation.
Use a systems medicine approach to understand inflammatory and other diseases.
Develop novel methods to facilitate exploration of unstructured datasets.
Write well-crafted, maintainable, scalable, and performant code.
Lead and carry out projects with minimal supervision.
Participate in writing papers and grant proposals.
Present project progress during group meetings.