Postdoctoral Research Fellow - Multiomics

Postdoctoral Research Fellow - Multiomics

Dana-Farber Cancer Institute

Boston, Massachusetts

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.

• 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 optimise 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.

• 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 modelling, 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.

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

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.

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