The Sarcoma Center at DFCI, in close partnership with the Getz Lab (Broad Institute) and the Janeway Lab (DFCI), is searching for an experienced computational biologist with additional experience and interest in cancer biology to play a lead role in projects focused on osteosarcoma and leiomyosarcoma. These projects are associated with the Cancer Moonshot funded Participant-Engagement Cancer Genomic Sequencing Network and aim to gain new insights into the genomics of these rare cancers, including treatment resistance. This particular role will focus on the genomic analysis primarily focused on leiomyosarcoma to identify unique genomic factors which impact oncogenesis, prognosis and response to treatment. The candidate will work on various genomic analyses across various data types such as whole-genome sequencing (WGS), whole-exome sequencing (WES), RNA sequencing, spatial data, etc, and will also include rich clinical annotation to explore the clinical implications of genomic findings. The analysis could include (but is not limited to) cancer driver discovery through genomic alteration analysis (e.g., structural variants), and spatial analysis.

We are seeking a highly motivated, creative, and talented researcher to dive right in and hit the ground running within the high-energy, fast-paced, and dynamic lab environments that value clinical impact and scientific rigor. Dr. Getz, Dr. Janeway, and Dr. Suzanne George, Chief of the Sarcoma Center at DFCI, place a high priority on mentoring postdoctoral trainees to work toward achieving their career paths and goals. Their labs, as well as the environments at the DFCI, the Broad Institute, and MGH, provide frequent and varied educational and skill-building opportunities.

About our labs:
The Sarcoma Center at DFCI led by Dr. Suzanne George is an internationally known multi-disciplinary program focused on clinical care and research to improve the lives of patients with sarcomas. Working across clinical and translational teams, the group has led the development of the majority of FDA drug approvals which have changed the standard of care in sarcomas and gastrointestinal stromal tumors (GIST). The team pioneered the early development of targeted therapies in sarcomas and has led the understanding of subsequent resistance mechanisms and lines of therapy. The Sarcoma Center continues to work closely with basic and translational labs across the world to better understand sarcoma biology and translate these findings into novel clinical approaches.

The Janeway Lab at DFCI is a dry lab headed by Dr. Katherine Janeway, Pediatric Oncology Section Chief. The lab performs research at the intersection of pediatric cancer patient care and genomics. We are interested in expanding the clinical impact of genomic discoveries, especially for children with solid tumors, with a specific focus on bone sarcomas. Because the cancers we study are rare, we use various approaches to build cohorts for genomic discovery including partnering directly with patients, building consortia, enterprise-level studies and data sharing.

The Getz Lab (at the Broad Institute and MGH) is a world-leading laboratory for cancer genome analysis. We develop highly innovative, robust, and widely-used computational methods to study the molecular basis of cancer, including genomic alterations that drive primary and resistant tumors, cell-of-origin, premalignant lesions, mutational processes, activity of different pathways, and microenvironmental changes. We then follow up key findings experimentally. While the comprehensive analysis of cancer genomes is ongoing, major barriers still exist in converting this information to patient benefit and achieving the goal of personalized medicine.

Our ideal candidate:

As a member of our teams, you will collaborate with other scientists, engineers, and clinicians with an emphasis on intellectual rigor. Indeed, our collective brainpower and creativity--our best asset--creates an excellent environment for deep innovation, out-of-the-box thinking, and creative problem solving. We will teach you what you do not yet know through mentoring, peer support, and many educational opportunities (e.g., floor talks, regular meetings, boot camps, journal clubs, conferences, etc.), and we will work together to make discoveries that help answer the most challenging questions in cancer. The ideal candidate will have a strong interest in rare cancers, which may require unique computational approaches due to small data sets, and also have an interest in the clinical translation of new findings. The candidate will have access to a robust clinical translational team, heavily involved in rare tumor drug development from early stage through registration enabling clinical trials.

The successful experienced candidate will bring strong computational and statistical skills (e.g., a background in Computational Biology, Biology, Machine Learning, Statistics, Medicine, Physics, Chemistry, Engineering, Mathematics, Computer Science, or other related fields) coupled with direct experience in computational research, as well as a healthy enthusiasm for learning on the job. In return, you will develop many core competencies to prepare you for the next stages of your career. Come and bring your energy, intellectual curiosity, and computational skills/talents to these world-class dynamic teams!


Role Expectations/Responsibilities
? Play a lead role in designing and executing data analysis strategies to support research projects involving multiple data types.
? Explore and develop tools for analyzing novel data types.
? Develop new methodologies for integrating data and predicting tumor outcome, subtypes, molecular mechanisms, and response to therapy.
? Conceive, implement and test statistical models; analyze data from experiments.
? Present results to a variety of audiences, including non-computational researchers.
? Prepare written reports (e.g., manuscripts, grants, patents) and presentations for meetings.
? Opportunity to teach and mentor junior team members.


Requirements

1. Bachelor's degree required. A PhD in Bioinformatics, Computer Science, Engineering, Mathematics, Statistics, Physics, or a related quantitative discipline preferred.

2. 2-3 years' experience in biologically focused research, with a preference on genomic analysis of cancer.

3. Fast learner, analytical thinker, creative, "hands-on", team-player.

4. Experience with computational analysis, algorithm development and statistics.

5. Proficiency in at least one modern programming language. Experience with a scientific programming environment (such as Python, R, or Matlab) is preferred.

6. Strong communication skills.

7. Background in machine learning or biology is a plus.

8. Knowledge of cancer genomics is a plus but is NOT required. Inclination to acquire such knowledge is imperative.


The Computational Biologist II is responsible for complex data analysis or processing of biological data, with a focus on high-throughput technologies and genomic databases.

The Computational Biologist is a quantitative scientist who collaborates with scientific investigators and with other research staff in the analysis of high-throughput data, and dissemination of scientific results.

The Computational Biologist may work on many types of projects and areas of research including cancer genomics, functional genomics, immuno-oncology, molecular imaging, data management and integration, and querying biological databases.

Located in Boston and the surrounding communities, Dana-Farber Cancer Institute is a leader in life changing breakthroughs in cancer research and patient care. We are united in our mission of conquering cancer, HIV/AIDS, and related diseases. We strive to create an inclusive, diverse, and equitable environment where we provide compassionate and comprehensive care to patients of all backgrounds, and design programs to promote public health particularly among high-risk and underserved populations. We conduct groundbreaking research that advances treatment, we educate tomorrow's physician/researchers, and we work with amazing partners, including other Harvard Medical School-affiliated hospitals.
 

PRIMARY DUTIES AND RESPONSIBILITIES:

• Data Processing:  Uses existing tools to build data processing pipelines to convert raw data into formats compatible with conventional statistical analysis and visualization. Adapts tools when necessary.
• Data Analysis:  Performs routine analysis for which established tools exist and are considered reliable.
• Keeps up with the computational biology literature to assure pipelines components are up to date. Adapts tools when necessary.
• Data and Software Management:  Monitors, downloads, organizes, and manages data from public data repositories or generated by collaborates. Evaluates published tools and updates pipeline as necessary. Writes scripts that perform this automatically.
• Manuscript Preparation:  Independently edits and drafts the computational biology sections of a manuscript; assists in writing the results section; checks manuscripts for numerical accuracy; prepares tables and figures. 
• Grant Preparation:  Helps to formulate specific aims, explains options for experimental design, and develops data analysis plans.   Minimal guidance is expected.
• Research Portfolio Management:  Develops timelines and components for larger projects; masters multi-tasking so that complex projects involving many interdisciplinary individuals move forward smoothly.
• Team interactions:  Share strategies for effective interaction with investigators, as well as for efficient task management.  Share analytic strategies with peers.  Suggest professional team initiatives.

KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED:

• Computational Skills:  Expert Knowledge of UNIX/Linux. Strong knowledge of scripting in Python and statistical programming using R.
• Data analysis Skills: Experience with principles of experimental design and the 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 - ability to effectively interact with all levels of staff and external contacts.
• Excellent analytical, organizational and time management skills.

SUPERVISORY RESPONSIBILITIES:  None

Minimum Education:
Bachelor's degree required in a STEM field.  Master?s degree preferred in bioinformatics, computational biology, statistics, biostatistics, computer science and/or the life sciences.

Minimum Experience:
2 years with Bachelor?s degree or 1 year with Master?s degree; academic research experience or authorship in scientific publications experience may substitute for work experience.

At Dana-Farber Cancer Institute, we work every day to create an innovative, caring, and inclusive environment where every patient, family, and staff member feels they belong. As relentless as we are in our mission to reduce the burden of cancer for all, we are committed to having faculty and staff who offer multifaceted experiences. Cancer knows no boundaries and when it comes to hiring the most dedicated and compassionate professionals, neither do we. If working in this kind of organization inspires you, we encourage you to apply.

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 characteristics protected by law.  

EEO Poster

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Pay Transparency Statement

The hiring range is based on market pay structures, with individual salaries determined by factors such as business needs, market conditions, internal equity, and based on the candidate?s relevant experience, skills and qualifications.

For union positions, the pay range is determined by the Collective Bargaining Agreement (CBA).

$85,000.00 - $105,000.00