Computational Biologist

Responsibilities

• Develop, innovate, and maintain advanced computational methods to process, analyze, and interpret large-scale single-cell genomics and perturbation datasets
• Collaborate with wet-lab and computational teams to integrate data from diverse experimental modalities and guide experimental design
• Build, optimize, and scale data analysis pipelines using modern cloud computing environments
• Contribute to data infrastructure, ensuring reproducibility, scalability, and efficient access to large datasets
• Communicate findings clearly through reports, visualizations, and presentations to multidisciplinary audiences

Requirements

• Ph.D. in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field, or equivalent experience
• Proficiency in Python, R, and Unix/Linux environments
• Demonstrated experience in single-cell or multi-omics data analysis
• Solid understanding of statistics, data modeling, and modern machine learning approaches
• Experience deploying and scaling computational pipelines on cloud platforms (AWS, GCP, or similar)

Preferred Qualifications

• Background in functional genomics, CRISPR screens, or perturb-seq analysis
• Experience integrating multi-source data to derive novel and impactful insights
• Expertise in data engineering and reproducible research tools (e.g., Docker, Nextflow, Snakemake)
• Experience with deep learning frameworks such as PyTorch or TensorFlow
• Strong publication record in computational methods or biological data analysis