Postdoctoral Research Fellow - Van Allen Lab

The Dana-Farber Cancer Institute seeks a POSTDOCTORAL COMPUTATIONAL BIOLOGIST AND DATA SCIENTIST FELLOW, under the Van Allen lab (http://vanallenlab.dana-farber.org/) to work on the analysis of new datasets generated in the context of multiple clinically oriented cancer sequencing projects in order help advance efforts for precision cancer medicine. As Dr. Van Allen is the Chief of the Division of Population Sciences, our research effort includes collaborative work with the division faculty members on identification of cancer risk, risk mitigation, early detection, prevention, delivery of cancer care and health policy. The Van Allen lab is an interdisciplinary and highly collaborative laboratory with diverse scientists from various scientific domains leading exciting cancer research.

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, HIV/AIDS 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.

The qualified candidate will specifically focus on new algorithms for the clinical integration of integrative molecular profiling and large-scale data sets (e.g. pathology images, clinical notes) to enable new discoveries in patients under multiple contexts. A specific focus on advancing algorithm development through emerging deep learning techniques is especially of interest. The candidate will also evaluate and integrate existing tools and databases into high-throughput pipelines, and facilitate the display and the distribution of processed data.

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Related projects and responsibilities will include:

• Creation of machine learning algorithms that effectively integrate molecular, pathology image, and clinical data for prediction and biological discovery, with an emphasis on prostate cancer

• Studies of non-coding and RNA-based drivers of cancer development and treatment response

• Studies of patient samples for tumor behavior and clinical outcomes in context of immunotherapy

These projects are collaborative efforts between the Dana-Farber Cancer Institute, the Broad Institute, and multiple other institutions. The goals of this initiative consist of analyzing sequencing data to determine the effects of genomic alterations and expression changes on clinical behavior, both retrospectively and prospectively. These new data could help identify novel approaches for personalized care in oncology. In addition, this data may provide support for new methods in clinical decision-making, biomarkers for rational drug development, and new insights into tumor biology through innovative analyses.

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The person hired for this position will join the team in this effort, and will participate in the design and implementation of algorithms to analyze the data and integrate with other data sets including clinical outcomes data. This person will also help with the generation of tools needed for manipulating and preparing data for display; transferring data to external collaborators and data repositories; and will also help maintain, support, and document shared tools, code base, and data sets. As the software infrastructure evolves, this position is likely to present diverse and flexible opportunities - from deeper and more complex software design problems, to becoming more involved in the bioinformatic and analytic aspects of predictive modeling.

• A Ph.D. in bioinformatics, genetics, statistics, mathematical, physical, or computer science, or comparable research experience, together with significant experience in computer programming and computational biological applications.
• A strong background in deep learning techniques, statistics and their potential applications to other domains like biology. Experience managing and curating large datasets desired.
• Excellent oral and written communication skills and the ability to perform both self-directed and guided research are required.
• Must demonstrate outstanding personal initiative and the ability to work effectively as part of a team.
• Ability to meet deadlines and efficiently multitask is a must.
• Ability to effectively collaborate across a range of individuals with different comfort toward computational biology, including oral and written communication skills.
• Ability to seek out mentorship and assistance as needed, while also being a mentor to other members of the community.

KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED:

• Machine Learning background
• Cancer biology background
• Experience in Python and/or R is preferred
• Experience with cloud computing
• Willingness to learn new languages and tools as the field grows

SUPERVISORY RESPONSIBILITIES:

This position will involve co-mentoring of students joining the group as described above, with opportunities for growth in developing multi-disciplinary teams that are project oriented.

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 equally committed to diversifying our faculty and staff. Cancer knows no boundaries and when it comes to hiring the most dedicated and diverse professionals, neither do we. If working in this kind of organization inspires you, we encourage you to apply.

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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.

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