Trách nhiệm chính

• Write code, build reproducible pipelines, and run rigorous statistical analyses to transform raw transcriptomic, proteomic, and imaging data into actionable insights.
• Deliver robust data workflows and publication‑quality visualizations for drug discovery scientists.
• Integrate proteomic data with transcriptomic findings to build comprehensive views of compound mechanisms and identify clinical biomarkers.
• Design and apply appropriate statistical methods for experimental design, power analysis, batch effect correction, and complex modeling.
• Collaborate with drug discovery, ML, and imaging scientists to translate biological questions into actionable analysis plans.
• Create interactive dashboards and clear visualizations to communicate complex results to scientific and non‑technical stakeholders.
• Leverage AI agents and LLM‑based tools to accelerate routine analyses and establish best practices across the team.

Yêu cầu

• PhD in Computational Biology, Bioinformatics, Biostatistics, Genomics, or a related quantitative field (or an MS with equivalent industry experience).
• 1‑3 years of industry experience, or 3+ years of in‑depth academic/research experience in genomic or other omics data analysis.
• Strong foundation in linear/generalized linear models, hypothesis testing, multiple testing correction, and handling of batch effects/confounders.
• Deep understanding of genomics or other omics data analysis within a biotech, biopharma, or deep technical academic setting.
• Hands‑on experience with end‑to‑end RNA‑seq analysis and proteomic data analysis (normalization, missing value handling, differential abundance).
• Proficiency in R and/or Python for data analysis and software development.
• Experience in software development best practices, reproducible research, and code management.
• Demonstrated ability to translate biological questions into data problems and present complex findings to cross‑functional teams.

Yêu cầu ưu tiên

• Experience analyzing biological image data (high‑content screening or microscopy).
• Experience applying machine learning to multi‑omic or imaging data.
• Publications and presentations in peer‑reviewed journals or scientific conferences.
• Familiarity with cloud computing environments (AWS, OCI) or HPC clusters.
• Experience with public biological data resources (GEO, TCGA, Gene Ontology, KEGG, Reactome).
• Hands‑on experience using AI agents/LLM‑based tools to support data analysis and code development.
• Workflow managers (e.g., Nextflow, Snakemake), containerization (Docker), and version control (Git).

Mức lương

• Thỏa thuận

Phúc lợi

• Competitive salary, negotiable based on experience, plus various allowances and benefits including lunch, living expenses, women’s allowance, Japanese language, IT certifications, etc.
• Performance bonuses, annual bonuses, and salary reviews twice a year.
• Hybrid working with flexible check‑in hours from 7:45 – 8:45 AM.
• Comprehensive health insurance with Sun* Care and seniority benefits.
• Women’s benefits: 2.5 hours of menstrual leave per month and 1 hour of childcare leave per day for employees with children under 1 year old.
• Annual company trips and quarterly team‑building activities.

Hình thức làm việc

• Hybrid working with flexible check‑in hours from 7:45 – 8:45 AM.

Thông tin khác

• Location: Hà Nội.