Computational Research Associate

Responsibilities

• Process and analyze large-scale single-cell and perturb-seq datasets using established computational pipelines
• Develop, document, and maintain reproducible analysis workflows and data processing infrastructure
• Support data management and organization across multiple internal and external datasets
• Collaborate closely with experimental and computational scientists to translate raw data into interpretable biological results
• Implement and optimize pipelines in cloud environments (e.g., AWS, GCP) for scalable data processing
• Maintain codebases, perform quality control on data outputs, and ensure reproducibility and traceability of analyses
• Generate clear reports, visualizations, and summaries to communicate results across teams

Requirements

• B.S. or M.S. in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field
• 2+ years of experience working with biological or single-cell datasets
• Proficiency in Python and/or R for data analysis and visualization
• Familiarity with standard genomics tools and file formats (FASTQ, BAM, HDF5, AnnData, etc.)
• Experience using and maintaining analysis pipelines in a Unix/Linux environment
• Experience working with cloud compute platforms (AWS, GCP, or similar)
• Strong organizational skills and commitment to clean, reproducible code

Preferred Qualifications

• Experience analyzing single-cell RNA-seq or perturb-seq datasets
• Familiarity with workflow management systems (Nextflow, Snakemake, or similar)
• Experience with containerization tools such as Docker
• Exposure to data engineering concepts
• Understanding of basic statistical methods for genomics data analysis