Associate Computational Biologist

The Raghavan Laboratory at the Dana-Farber Cancer Institute (DFCI) and Harvard Medical School is seeking a highly motivated and collaborative full-time computational biologist with a Bachelor’s or Master’s degree in Computational Biology, Bioinformatics, Biology, Biomedical Engineering, or related field to join the group.  The Raghavan lab investigates how tumor cell states shape cancer cell behaviors, microenvironmental interactions, and therapeutic sensitivity and resistance, with a primary focus in pancreatic and biliary cancers. We apply a variety of techniques including genomic, RNA, and single-cell sequencing of patient samples and cell models, high throughput drug testing, and CRISPR engineering with the long-term goal of identifying new state- and context-specific cancer vulnerabilities. We work closely with clinicians in the Gastrointestinal Cancer Center at DFCI to combine clinical observations and patient-derived data with rigorous basic science investigation to identify impactful translational advances that ultimately improve patient care.

Located in Boston and the surrounding communities, Dana-Farber Cancer Institute brings together world renowned clinicians, innovative researchers and dedicated professionals, allies in the common mission of conquering cancer and related diseases. Combining extremely talented people with the best technologies in a genuinely positive environment, we provide compassionate and comprehensive care to patients of all ages; we conduct research that advances treatment; we educate tomorrow's physician/researchers; we reach out to underserved members of our community; and we work with amazing partners, including other Harvard Medical School-affiliated hospitals. This position is offered at the Dana Farber Cancer Institute in partnership with the Broad Institute of Harvard and MIT, located in Cambridge, MA. DFCI and the Broad Institute bring together world-renowned clinical and technological expertise to study cancer and to develop novel therapeutic approaches.

Dana-Farber Cancer Institute is an equal opportunity employer and affirms the right of every qualified applicant to receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, national origin, sexual orientation, genetic information, disability, age, ancestry, military service, protected veteran status, or other groups as protected by law.

Disclaimer

The information on this description has been designed to indicate the general nature and level of work performed by employees within this classification.  It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job.  Requirements are subject to possible modification to reasonably accommodate qualified individuals with disabilities.  This document does not create an employment contract, implied or otherwise, other than an “at will” employment relationship.

This individual will work with computational biologists, research technicians, graduate students, and post-doctoral fellows to analyze genomic, transcriptomic, and pharmacologic data in a highly collaborative and multi-disciplinary research environment. This experience will enable the candidate to advance their skills in computational methods and cancer biology with an eye toward translational applications for cancer care. The ability to work independently and to master a variety of programming and analytical techniques is essential for this role, as are good organizational and communication skills, a desire to learn new scientific approaches, and the ability to function effectively within a team. Candidates will have opportunities to pursue combined wet-lab and computational projects if interested. Individuals will be authors on manuscripts published by the laboratory, and will assist in analysis of data for manuscript and grant figures along with writing as appropriate.  Highly motivated and talented computational biologists will be given increasing responsibility and may eventually lead projects. She/he will also help with maintenance of lab computational pipelines, data storage, and infrastructure. She/he will meet regularly with Dr. Raghavan to assess progress and receive mentorship and guidance.

Specific duties may include:

1. Data Processing: Use existing tools to build data processing pipelines to convert raw data into formats compatible with conventional statistical analysis and visualization.
2. Data Analysis: Perform routine analysis for which established tools exist and are considered reliable.  Keep up with the computational biology literature to assure pipelines components are up to date. This will include analysis of targeted and whole exome/genome sequencing datasets, bulk and single-cell RNA-sequencing data, and pharmacologic and functional genomics (e.g., CRISPR screening) datasets.
3. Data and Software Management: Monitor, download, organize, and manage data from public data repositories or generated by collaborations, and prepare datasets for public repository upload. Evaluate published tools and update pipelines as necessary, including for analysis of cell line and organoid drug response data. This will also include organization and management of laboratory databases and compute infrastructure.
4. Manuscript Preparation: Draft the computational biology sections of a manuscript; assist in writing the results section; check manuscripts for numerical accuracy; prepare tables and figures. 
5. Grant Preparation: Help to formulate specific aims, analyze preliminary data, prepare figures, explain options for experimental design, and develop data analysis plans.  
6. Research Portfolio Management: Develop timelines and components for multiple routine projects; master multi-tasking so that complex projects involving many interdisciplinary individuals move forward smoothly.
7. Team interactions: Offers peer-to-peer training for new statisticians in design, analysis, and presentation of results.  It is expected that insight into career growth will be offered to more junior statisticians.
   
   

Knowledge, Skills, and Abilities Required:

• Computational skills: Knowledge of UNIX/Linux. Familiarity with scripting in Python and statistical programming using R.
• Data analysis skills: Familiarity with principles of experimental design and modern data analysis paradigms is required.
• Collaboration: Able to discuss and present results, share ideas accurately and communicate them effectively, both in writing and verbally.
• Strong interpersonal skills: Able to effectively interact with all levels of staff and external contacts.
• Excellent analytical, organizational and time management skills.

To apply, please submit a letter of interest, resume/CV, transcript, and list of 3 references.