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Bioinformatics Technician I - Sun Lab (Relocation ...

Massachusetts Institute of Technology - Cambridge, MA

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Job Description

Classification: Exempt Job Family: Technicians Reports to: AI Whitehead Fellow Job Description Summary: Collaborate on short and long term independent research projects to support scientific research objectives of the lab. Utilize programming skills to design and implement tools directly related to biological research. The research includes the analysis of high throughput sequencing data, development of code and algorithms to study questions related to human genetics and using statistical tools to evaluate different hypothesis This is a two-year term position, with the possibility of renewal contingent on performance and funding. OVERALL RESPONSIBILITY Collaborate on short- and long-term research projects to support the scientific objectives of the laboratory. Apply computational, statistical, and machine-learning approaches to analyze large-scale biological datasets, with a focus on single-cell and spatial genomics. Design, implement, and maintain analysis pipelines and computational tools that directly support biological discovery. Contribute to hypothesis-driven research by integrating computational analyses with experimental data. RESEARCH BACKGROUND AND GOALS The Sun Lab seeks a highly self-motivated Bioinformatics Technician with strong computational skills and a keen interest in applying AI and machine learning to biological questions. Our research centers on developing and applying advanced computational and data-driven methods to analyze large-scale single-cell and spatial omics datasets, with the goal of understanding cell-cell communication, brain-immune interactions, and genotype-phenotype relationships in health and disease. The successful candidate will play a key role in analyzing high-dimensional datasets, implementing machine-learning-based approaches, and developing reproducible bioinformatics workflows. This position offers hands-on exposure to cutting-edge AI-for-biology research, close collaboration with experimental scientists, and the opportunity to contribute to high-impact studies of diseases with strong clinical relevance. CHARACTERISTIC DUTIES • Maintain, optimize, and extend pipelines for single-cell RNA-seq, single-nucleus RNA-seq, and spatial transcriptomics data • Develop and implement computational and machine-learning-based methods for large-scale biological data analysis • Integrate diverse data types (e.g., single-cell, spatial, genetic, and phenotypic data) to address complex biological questions • Perform statistical analyses and model evaluation to test biological hypotheses • Create clear documentation, reproducible workflows, and data visualizations • Manage data organization, versioning, and computational resources • Present results to internal lab members and external collaborators QUALIFICATIONS • BSc or MSc (or equivalent) in Computational Biology, Bioinformatics, Genome Science, Computer Science, AI, or a related discipline with a strong biological focus • Demonstrated research experience with single-cell and/or spatial omics datasets (e.g., scRNA-seq, snRNA-seq, MERFISH, Xenium, Slide-seq, or similar technologies) • Experience applying machine learning, statistical modeling, or AI approaches to biological data analysis • Strong programming experience in at least two languages (e.g., Python, R, shell scripting) • Proficiency working in UNIX/Linux-based computing environments • Ability to work independently, manage multiple tasks, and solve technical problems effectively • Strong communication skills and ability to collaborate across computational and experimental teams • Experience documenting analyses and maintaining reproducible computational workflows Pay Range Minimum: $55,000 Pay Range Maximum: $75,000 Whitehead Institute is an E-Verify employer

Created: 2026-03-04

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