Postdoctoral Research Fellow - Computational Functional Genomics - Gillani Lab

Location: 100% onsite in Boston, Massachusetts, United States

Salary: $72,000–$76,385 per year

Company

hirify.global conducts cancer research and provides patient care, collaborating with Harvard-affiliated hospitals and other research institutions.

What you will do

• Analyze whole-genome, transcriptomic, epigenomic, and single-cell sequencing data from pediatric cancer tumor samples.
• Study cancer therapy resistance, tumor behavior, and clinical outcomes using patient-derived data.
• Design and implement artificial intelligence and machine learning algorithms for biologically and clinically motivated oncology questions.
• Develop data-processing tools, algorithms, and high-throughput pipelines, integrating external tools, databases, and clinical outcomes data.
• Prepare data for visualization, transfer datasets to collaborators and repositories, and maintain shared code, tools, and datasets.
• Lead collaborative computational pediatric cancer research projects through completion and publication while co-mentoring students.

Requirements

• Ph.D. in genetics, computational biology, statistics, computer science, biomedical engineering, mathematics, or a related discipline; M.D. candidates with comparable research experience are also considered.
• Significant computational biology research experience, including R and/or Python and cloud computing.
• Strong background in statistics and biology, with experience managing and curating large datasets.
• Strong communication, collaboration, initiative, multitasking, and self-directed research skills.
• Ability to collaborate across computer science, clinical medicine, and other disciplines.
• Ability to work onsite in Boston to support collaboration, learning, and research progress.

Culture & Benefits

• Collaborative projects with the hirify.global, Broad Institute, Boston Children's Hospital, Harvard Medical School, and other institutions.
• Work in an environment focused on respectful, inclusive, diverse, and equitable collaboration.
• Opportunities to develop multidisciplinary, project-oriented teams and mentor students.
• Potential to contribute to personalized oncology, clinical decision-making, biomarker development, and new cancer treatments.