Postdoctoral Research Fellow - Computational Biology - Ghobrial Lab

Dana-Farber Cancer Institute; Boston (MA); On-site; USD 46,000 - 76,000; Full time

Job summary

Dana-Farber Cancer Institute in Boston seeks a Postdoctoral Research Fellow to conduct computational research on multiple myeloma and precursor conditions, developing predictive models from multi-omics data. The role emphasizes collaboration with clinicians and wet-lab scientists, and mentorship of junior researchers.

Located in Boston, the institute fosters inclusive excellence and aims to advance treatment through cutting-edge data science, AI, and translational research within the Dana-Farber

Qualifications

• PhD in Bioinformatics, Computational Biology, Systems Biology, Statistics, Computer Science, or related field; or MD with 2-3 years experience.
• Strong programming skills in Python, R, or equivalent, with experience in data analysis, statistics, and machine learning.
• Experience with multi-omic data integration frameworks, predictive modeling of clinical outcomes, and network-based analysis to identify biomarkers.
• Experience with RNA-seq, ATAC-seq, spatial transcriptomics, single-cell data, etc., familiarity with basic wet lab approaches.
• Background in cancer biology, immunology, and/or patient-derived datasets is a plus; capable of conceiving and leading projects.

Responsibilities

• Conceive, implement, and test statistical, ML, and network-based analyses of high-dimensional biological data.
• Design and optimize predictive models of drug response by integrating multi-omics and clinical data.
• Interpret findings and present at scientific meetings; guide project direction with PI.
• Collaborate with computational/clinical teams and external partners to translate results into actionable insights.
• Maintain meticulous notebooks and documentation for reproducibility.
• Contribute to grant applications, manuscripts, and progress reports; prepare figures and data.
• Mentor junior team members on analytical approaches and professional development.

Skills

Python

R

Statistics

Machine learning

Team collaboration

Scientific communication

Education

PhD in Bioinformatics/Computational Biology/Statistics or related

MD with 2-3 years related experience

Tools

Multi-omics frameworks

Genomics tools

Transcriptomics tools

Network analysis tools

Job description

The lab of Dr. Irene Ghobrial is seeking a highly motivated Postdoctoral Research Fellow to conduct computational research and lead projects focusing on multiple myeloma and its precursor conditions.

Based on the mission of the Ghobrial lab, the successful candidate will be responsible for identifying novel biomarkers for tumor burden, tumor biology, and immune state in both the bone marrow and peripheral blood aiming to improve assessment for prognostication and monitoring of therapy response in patients with monoclonal gammopathy of unknown significance (MGUS) and smoldering multiple myeloma (SMM).

In pursuit of these goals, the successful applicant will leverage human sample data continuously generated in the lab for multi-omic analysis (including genomic, transcriptomic, and proteomic), including samples derived from clinical trials. The successful candidate will work at the intersection of computational biology, genomics, proteomics, pathology, artificial intelligence, and clinical data science, contributing to projects that leverage cutting-edge multi-omic datasets to develop predictive models of therapy response and identify clinically actionable biomarkers. Beyond fundamental research there is also strong interest in leveraging emerging data for drug discovery in the context of the larger DFCI ecosystem.

The successful candidate will be highly organized, a team player, and able to work flexible hours to accommodate experimental needs. We are looking for a bright, motivated, and dedicated individual with strong scientific, organizational, and interpersonal skills.

This post-doctoral position is available to start at any time.

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.

Qualifications

• PhD in Bioinformatics, Computational Biology, Systems Biology, Statistics, Computer Science, or related field; or M.D. with at least 2-3 years of related experience.
• Strong programming skills in Python, R, or equivalent, with experience in data analysis, algorithm development, statistics, and machine learning.
• Experience with multi-omic data integration frameworks, predictive modeling of clinical outcomes (e.g., therapy response), and network-based analysis to identify biomarkers.
• Experiencewith one or more multi-omic data types (e.g. RNA-seq, ATAC-seq, spatial transcriptomics, single-cell data, etc…) and familiarity with basic wet lab experimental approaches.
• Background in cancer biology, immunology, and/or working with patient-derived datasets is a plus, as is experience conceiving and leading biologic/clinical projects.
• Highly collaborative, with ability able to work on projects alongside fellow bioinformaticians, wet-lab experimentalists, and clinicians.
• The candidate must be self-motivated, highly organized, collaborative, flexible and demonstrates excellent scientific, interpersonal, and communication skills.

Responsibilities

• Conceive, implement, and test statistical, machine learning, and network-based approaches to analyze high-dimensional biological data, including genomic, transcriptomic, and proteomic datasets, ensuring methods are robust, reproducible, and appropriately validated.
• Design, build, and optimize predictive models of drug response by integrating multi-omic and clinical data, iterating on model architecture and features to improve accuracy, interpretability, and clinical relevance.
• Regularly interpret research findings to inform project direction and priorities, in close discussion with the Principal Investigator. Present research findings at scientific conferences and other scientific meetings.
• Collaborate closely internally with computational and clinical teams to interpret results and translate findings into actionable insights. Collaborate closely with external academic and industry partners.
• Maintain detailed, accurate, and well-organized laboratory notebooks and research documentation to support reproducibility and continuity.
• Contribute to grant applications, manuscripts, progress reports, and other scientific communications, including preparation of figures and supporting data.
• Mentor junior team members, providing guidance on analytical approaches and supporting their professional development.

At Dana-Farber Cancer Institute, we work every day to create an innovative, caring, and inclusiveenvironment 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 compassionateprofessionals, neither do we.

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