Postdoctoral Research Fellow - Van Allen Lab

The Dana-Farber Cancer Institute seeks a POSTDOCTORAL RESEARCH FELLOW, under the Van Allen lab ((Use the "Apply for this Job" box below).) 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 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.

The qualified candidate will focus on developing new algorithms, including agentic artificial intelligence approaches, for the clinical integration of integrative molecular profiling and large-scale datasets (e.g. pathology images and clinical notes) to enable new discoveries across multiple patient contexts. A specific focus on advancing algorithm development through emerging deep learning techniques is of strong 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.

Related projects and responsibilities will include:

• Creation of artificial intelligence algorithms that effectively integrate molecular, pathology/image, and clinical data for prediction and biological discovery
• Prospective clinical sequencing to guide the care of cancer patients
• Studies of coding, non-coding, RNA, and spatial-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.

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, mathematics, physics, or computer science, or comparable research experience, along with significant experience in machine learning, computer programming, computational biological applications.
• A strong background in statistics and biology. Experience managing and curating large datasets and with machine learning techniques 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.

• Background in machine…