Computational Scientist II - VallabhMinikel Lab

The Vallabh/Minikel lab located at the Broad Institute of MIT and Harvard seeks a Computational Biologist II to join the team. The lab is led by Dr. Sonia Vallabh and Dr. Eric Minikel who became scientists in response to Sonias own genetic test report. The goal of our work is to discover develop characterize and advance effective treatments for prion disease a rapidly fatal and currently incurable neurodegenerative disease. You can read more about our mission here: g/

The successful applicant will provide dynamic computational support to multiple diverse translationally relevant projects in the lab. We aspire for this individuals work to contribute directly to the development of a therapy for a currently untreatable disease. To seize this opportunity they must be a selfstarter highly motivated to contribute to the mission of our lab. Being mission driven means that the lab is dynamic with task lists evolving rapidly depending on what is most helpful at any given time. It also means that we must all bring to work every day the attitude that no task is below us. Some of our projects involve big data. Some involve small data. We work with wideranging data types from genomics transcriptomics metabolomics and proteomics to imaging to singlereadout experiments in cells and small cohorts of animals and patients. Were a vertically integrated lab that is constantly forging ahead onto new ground. Were here to do whats needed in service of a lifesaving drug in our lifetimes. We are primarily a wet lab and the successful applicant will need to be able and enthusiastic to work closely alongside wet lab biologists in a spirit of collaboration and without snobbery. They must bring a spirit of critical thinking be able to troubleshoot independently and take an active role in seeking advice and guidance as needed.

The Broad is rich with computational resources and expertise and Dr. Minikel who trained as a computationalist will supervise this individual. However it bears repeating that we are primarily a wet lab to make the most of this role the applicant will need to be creative proactive interpersonally aware and teamspirited across disciplinary lines.

Qualifications

PhD in Biology Computer Science Bioinformatics Engineering Math Statistics Physics or a related quantitative discipline

Knowledge of biology spanning omics to epidemiology

Experience with Linux command line environments and strong knowledge of statistics and computational data analysis (R Python)

Comfort with multicontributor collaboration via GitHub

Robust oral and written communication skills. We all represent the lab and mission.

Outstanding critical thinking skills

Willingness and ability to quickly gain new skills and knowledge in relevant domains is a must

Strong interpersonal and collaboration skills to work in a teamoriented environment

Ability to skillfully work through differences in perspective

A selfstarting attitude

Ability to report on progress in a professional manner on a regular basis

Exquisite attention to detail and organizational capacity.

Responsibilities

The successful candidate will:

Apply statistical methods to a variety of genomic transcriptomic metabolomic proteomic and imagebased profiling datasets.

Help to think critically about interpretation contextualization and visualization of these data.

Help to maintain organization of the labs data across data types.

Coordinate with sequencing and imaging facilities to receive organize conduct quality control and preprocess of the data.

Generate data visualizations and assist the team with the effective graphical communication and representation of the findings.

Provide supervision to a Computational Associate 1.

Develop new analytical approaches visualization tools and automation approaches for routine analysis tasks.

Advise wet lab scientists on strategies for ensuring the datasets they generate are clean and analysisready.

Listen to problems and challenges from wet lab scientists and advise on experimental design appropriate statistical tests QC approaches dataviz strategies and automation opportunities.

Prepare analytical pipelines to be applied on local and cloudbased computational platforms.

Prepare reproducible git repositories for public release with commented code organized analytical datasets and clear READMEs.

Prepare summary reports and communicate results to scientists in the lab.

Join calls with outside collaborators as necessary prepared to present professionally.

Contribute to preparation of manuscripts and drafting of analytical methods.

Flexibly support collaborating labs as needed.

The following examples of public repositories from our lab will help the candidate to get a sense of the computational component of past projects in our lab:

encourage candidates to apply as early as possible and will review applications on a rolling basis. Required application documents include a cover letter and CV. Please write a cover letter! Our lab is a unique environment and we want to get a feel for why you are interested in working here in particular. References will be requested on followup. We regret that we will not be able to reply to every applicant. Contact: Sonia Vallabh

We think this is an unusual and exciting opportunity for a Computational Biologist to get ontheground experience supporting rare disease drug development at the fastpaced intersection of academia and industry. If you think so too we would love to hear from you.