Postdoctoral Research Fellow - Computational Biologist

Overview

The Center for Functional Cancer Epigenetics (CFCE) is looking for a highly motivated and talented postdoctoral scientist with a strong computational background to join the Department of Medical Oncology at the Dana-Farber Cancer Institute. The candidate for this position will join a team of biologists analyzing single cell and spatial transcriptomic datasets using advanced artificial intelligence and machine learning (AI/ML) methods to advance efforts for translational cancer genomics and precision cancer medicine. We are seeking biomarkers to predict bladder cancer patient response to I/O therapy by analyzing high resolution imaging and single cell data from patient tumors with sophisticated machine learning approaches. These datasets will provide support for new methods in clinical decision-making, biomarkers for rational drug development, and new insights into tumor biology through innovative analyses.

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.

Responsibilities

• Apply existing and novel AI/ML approaches to cancer single cell and spatial transcriptomic datasets. Includes understanding data quality metrics, analysis of H&E images and transcriptional data from a large cohort of bladder cancer patients and critically reviewing results.
• Implement and run best-practice methods in programming languages (Python, R) in local and cloud-based analysis platforms.
• Work together with team of biologists and clinical scientists to analyze datasets, generate data visualizations, and test hypotheses as part of our biomarker project.
• Maintain and document computational pipeline/scripts and analyses using appropriate tools and GitHub repositories.
• Communicate with key stakeholders (including clinicians and external collaborators) the results of data analyses.

Qualifications

• PhD in Biology or computer science or related field.
• Experience with AI/ML methods for image and/or genomic analysis.
• Experience with programming languages like Python, R, shell scripting, Snakemake, etc.
• Experience with high throughput next-generation sequencing data a plus.
• Excellent oral, written, and organizational skills are essential in addition to the ability to be independent and proactive.
• Ability to adapt plans and priorities to rapidly shifting project goals

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)

$72,000 - $76,385

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.