Postdoctoral Research Fellow - Multiomics

Dana-Farber Cancer Institute; Boston (MA); On-site; USD 72,000 - 76,385; Full time

Job summary

Dana-Farber Cancer Institute in Boston seeks a highly motivated Postdoctoral Research Fellow to join the Center for Functional Cancer Epigenetics. The project focuses on multiomic analyses and developing predictive models of therapy response using clinical trial data.

You will collaborate with computational biology, genomics, and clinical teams, implement pipelines, and contribute to publications and grant applications.

Qualifications

• PhD in Bioinformatics, Computational Biology, Systems Biology, Statistics, Computer Science, or related field.
• Strong programming skills in Python, R, or equivalent, with experience in data analysis, statistics, and machine learning.
• Experience with multiomic datasets (RNA-seq, ATAC-seq, ChIP-seq, spatial transcriptomics, single-cell).
• Familiarity with data integration frameworks, predictive modeling, and network analysis.

Responsibilities

• Develop and implement computational pipelines for integration of multiomic datasets.
• Apply statistical, ML, and network-based approaches to high-dimensional data.
• Collaborate with experimental and clinical teams to translate findings into insights.
• Design and optimize predictive models of drug response, including digital twin simulations.
• Contribute to manuscript writing and dissemination of findings.

Skills

Programming in Python or R

Multiomic data analysis

Data integration frameworks

Cloud computing/HPC

Education

PhD in Bioinformatics/Computational Biology/Statistics/CS

Tools

Snakemake

HPC environments

Job description

We are seeking a highly motivated Postdoctoral Research Fellow to join the Center for Functional Cancer Epigenetics (CFCE) at Dana‑Farber Cancer Institute and become part of a multidisciplinary project led by Paloma Cejas and Henry Long, in collaboration with AITIA, an artificial intelligence and computational biology company. The project focuses on understanding patient responses to drug treatments through multiomic analyses, including chromatin profiling, single‑cell sequencing, and spatial transcriptomics, using samples derived directly from clinical trials. The successful candidate will work at the intersection of computational biology, genomics, epigenomics, artificial intelligence, and clinical data science, contributing to projects that leverage cutting‑edge multiomic datasets to develop predictive models of therapy response and identify clinically actionable biomarkers.

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.

Key Responsibilities

• Develop and implement computational pipelines for the integration of multiomic datasets, including transcriptomics, chromatin profiling, genomics, spatial transcriptomics, and single‑cell data.
• Apply statistical, machine learning, and network‑based approaches to analyze high‑dimensional biological data.
• Collaborate closely with experimental and clinical teams to interpret results and translate findings into actionable insights.
• Design and optimize predictive models of drug response, including the use of digital twin simulations.
• Assist in data visualization, interpretation, and presentation of results for publications, grant applications, and internal/external meetings.
• Maintain rigorous documentation, reproducibility, and quality control of computational workflows.
• Contribute to manuscript writing and dissemination of research findings.

Qualifications

• PhD in Bioinformatics, Computational Biology, Systems Biology, Statistics, Computer Science, or related field.
• Strong programming skills in Python, R, or equivalent, with experience in data analysis, statistics, and machine learning.
• Experience with multiomic datasets, including RNA‑seq, ATAC‑seq, ChIP‑seq, spatial transcriptomics, and single‑cell data.
• Familiarity with data integration frameworks, predictive modeling, and network analysis.
• Experience with cloud computing, workflow management (Snakemake), or HPC environments is a plus.
• Strong analytical and problem‑solving skills, with attention to detail.
• Excellent communication and teamwork skills, with ability to collaborate across experimental and computational groups.

Preferred to have

• Experience in translational research or working with patient‑derived datasets.
• Familiarity with chromatin biology or epigenetics.
• Background in biomarker discovery or predictive modeling in oncology.

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. If working in this 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

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).

$72,000.00 - $76,385.00