Senior Computational Biologist

ABOUT THE ROLE

We are looking for a hands-on Computational Biologist to work extensively with transcriptomic, proteomic, and imaging data. In this role, you will play a key role in our biological research by writing code, building reproducible pipelines, and running rigorous statistical analyses to turn raw, complex datasets into actionable insights.

You will deliver robust data workflows and clear, publication-quality visualizations. Your hands-on analyses will directly enable our drug discovery scientists to understand disease mechanisms at the molecular level and make evidence-based decisions for our life-saving therapeutic programs.

WHAT WE DO

– RNA-seq Data Analysis: Perform end-to-end RNA-seq analysis, including quality control, quantification, normalization, differential expression, and pathway/gene set enrichment analysis.

– Multi-omics Integration: Analyze proteomic data and integrate it with transcriptomic findings to build a comprehensive view of compound mechanisms of action and identify clinical biomarkers.

– Statistical Modeling: Design and apply appropriate statistical methods for various studies, handling experimental design, power analysis, batch effect correction, and modeling complex experimental designs.

– Pipeline Development: Develop, validate, and maintain reproducible, production-grade analysis pipelines in collaboration with Data Engineering teams.

– Cross-functional Collaboration: Partner with drug discovery scientists to translate biological questions into actionable analysis plans, and work with ML/Imaging scientists to link image-derived features to molecular profiles.

– Data Visualization & Reporting: Create clear, publication-quality visualizations and interactive dashboards to communicate complex results to both scientific and non-technical stakeholders.

– Innovation via AI: Leverage AI agents and LLM-based tools to accelerate routine analyses, establishing best practices for their responsible use across the team.

WHO YOU ARE

*** Must have

1. Education & Domain Experience

– A PhD in Computational Biology, Bioinformatics, Biostatistics, Genomics, or related quantitative field, or an MSc with equivalent experience.

– 1-3 years of industry experience, OR 3+ years of in-depth academic/research experience in genomic or other omics data analysis

– Experience working with genomic/omics data in biotech, biopharma, or a technically advanced academic/research environment.

– Strong biological background.

2. Core Computational Biology Skills

– Hands-on experience with Bulk RNA-seq analysis, including QC, normalization, differential expression and pathway/gene set enrichment.

– Strong experience with standard RNA-seq tools such as DESeq2 and/or edgeR.

– Hands-on experience with proteomic data analysis, including normalization, missing value handling and differential abundance analysis.

– Experience integrating transcriptomic and proteomic data.

3. Statistics & Machine Learning

– Strong foundation in statistical methods, including experimental design, hypothesis testing, multiple testing correction, batch effects and confounders.

– Working knowledge of basic machine learning methods, including Elastic Net, Random Forest and XGBoost.

4. Programming & Pipeline Development

– Basic to strong proficiency in R or Python programming.

– Experience with Docker.

– Experience developing or working with automated analysis pipelines using Nextflow or Snakemake.

– Familiarity with version control such as Git.

5. Communication

– Ability to translate biological questions into analytical approaches and communicate findings to scientific and cross-functional teams.

*** Nice to have

– Experience analyzing biological imaging data, particularly immunofluorescence or microscopy data.

– Experience applying machine learning to multi-omics or imaging data beyond the core methods above.

– Experience with cloud computing or HPC environments.

– Experience with public biological data resources such as GEO, TCGA, Gene Ontology, KEGG, Reactome.

– Publications in peer-reviewed journals or presentations at scientific conferences.

– Experience using AI-assisted tools/LLMs to support data analysis or code development.

BENEFITS AND PERKS

Why this role

– Solve real-world biology problems: Analyze complex biological datasets, including transcriptomics, proteomics, cellular imaging, and compound data, to generate insights that support scientific research.

– Collaborate with scientific stakeholders: Work closely with domain experts and AI specialists to interpret analytical findings, communicate scientific insights, and support informed research decisions.

What Sun* offers

1. Technology Leadership & AI-Driven Development

– Hands-on AI-Driven Development: Work directly in an AI-Driven Development environment, applying AI throughout the software development lifecycle (from Requirements Analysis and Coding to Testing and Operations) with standardized solutions and processes developed by Sun*.

– Access to Advanced AI Tools: Gain access to premium AI tools such as GitHub Copilot, Gemini, Claude, etc., depending on project requirements, to automate tasks and maximize productivity.

– AI-Empowered Professional Development: Join in-depth AI-DD training courses and hands-on workshops designed to help employees strengthen their core expertise while mastering next-generation AI tools.

2. Empowerment Culture & Clear Career Growth

– Open & Creative Environment: A culture that values individuality, embraces experimentation and risk-taking, and encourages collaboration with like-minded colleagues who aspire to create positive social impact.

– Structured Career Path: Personalized career development toward either a Technical Expert or Management career track.

– Goal Setting & Empowerment: Support in defining individual and team goals through regular Goal Define Support sessions every 3 – 6 months, while empowering employees to take ownership of their work.

– Diverse Learning Ecosystem: Free access to learning platforms such as Udemy and LinkedIn Learning, Tech Expert seminars, and knowledge-sharing & cultural clubs.

3. Competitive Benefits & Comprehensive Well-being

– Salary & Allowances: Competitive salary, negotiable based on experience, plus various allowances and benefits, including lunch, living expenses, women’s allowance, Japanese language, IT certifications, etc.

– Bonuses & Performance Review: Performance bonuses, annual bonuses, and salary reviews twice a year.

– Flexible Working: Hybrid working with flexible check-in hours from 7:45 – 8:45 AM.

– Healthcare & Seniority Benefits: 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.

– Team Activities & Engagement: Annual company trips and quarterly team-building activities.

Contact: Trinh - 0868216798

Note: By applying for this position, you consent to Sun* collecting, storing, and processing your personal data for current and future recruitment purposes. Your data may be shared with relevant parties involved in the recruitment process and retained indefinitely until you submit an official written request for data deletion. For details regarding your rights and how your data is protected, please refer to [Sun*’s Personal Data Protection Policy here]