Postdoctoral Research Fellow - Computational Biology (Cancer Research)

Location: Boston, Massachusetts, United States; onsite with occasional remote work

Salary: $72,000–$76,385 per year

Company

hirify.global conducts cancer research, provides patient care, and advances treatment through collaborations with Harvard Medical School-affiliated hospitals.

What you will do

• Lead computational research projects focused on multiple myeloma and precursor conditions.
• Analyze genomic, transcriptomic, proteomic, and clinical datasets, including clinical-trial samples.
• Develop and validate statistical, machine learning, and network-based methods for high-dimensional biological data.
• Build predictive models of drug and therapy response and identify clinically actionable biomarkers.
• Collaborate with computational, clinical, wet-lab, academic, and industry partners.
• Prepare manuscripts, grants, reports, figures, presentations, and reproducible research documentation while mentoring junior team members.

Requirements

• PhD in Bioinformatics, Computational Biology, Systems Biology, Statistics, Computer Science, or a related field, or an MD with at least 2–3 years of related experience.
• Strong programming skills in Python, R, or an equivalent language.
• Experience with data analysis, algorithm development, statistics, machine learning, and predictive modeling.
• Experience integrating multi-omic data and working with one or more data types such as RNA-seq, ATAC-seq, spatial transcriptomics, or single-cell data.
• Ability to work collaboratively, independently, flexibly, and with strong scientific and communication skills.
• Work is based in Boston with onsite attendance and occasional remote work.

Nice to have

• Background in cancer biology, immunology, or patient-derived datasets.
• Experience with wet-lab approaches or leading biological and clinical projects.

Culture & Benefits

• Collaborative environment spanning computational biology, clinical research, pathology, genomics, proteomics, artificial intelligence, and clinical data science.
• Opportunities to contribute to cancer research, drug discovery, and clinically relevant scientific projects.
• Inclusive, diverse, and equitable workplace focused on patient care, research, and education.
• Flexible hours may be needed to accommodate experimental requirements.