Bioinformatics / Data Scientist - Single-Cell & Multimodal Data Analysis | Life Sciences

Location: one-north, Singapore (on-site)

Business Unit: Life Sciences

Employment Type: Full-time, Permanent

Reporting to: Head of AI for Science (AI4S) R&D (US)

About the Company

Galatek is a Singapore-headquartered deep technology company focused on enabling the next generation of scientific discovery and advanced manufacturing. Combining artificial intelligence, precision engineering, advanced optics, and software platforms, we develop intelligent systems that help organizations operate with greater precision, productivity, and insight.

As science and industry become increasingly interconnected, Galatek is building the intelligent infrastructure that empowers breakthrough discoveries, accelerates industrial progress, and contributes to a more sustainable future. Operating across Asia, Europe, and North America, we partner with customers worldwide to transform complex workflows into intelligent, scalable, and future-ready systems.

About the Role

As a Bioinformatics Scientist – Single-Cell & Multimodal Data Analysis, you will support Galatek's AI-driven biological research initiatives by analyzing and interpreting data generated from automated cellular experiments. Working closely with experimental scientists and AI researchers, you will develop bioinformatics workflows for processing single-cell transcriptomics, drug perturbation data, and quantitative cellular phenotypes.

A key focus will be generating high-quality, well-annotated biological datasets to support our emerging virtual-cell research direction, where experimental measurements are used to understand and predict cellular responses to perturbations.

This role offers an opportunity to work at the intersection of experimental biology, laboratory automation, and AI-driven scientific discovery.

Key Responsibilities

• Single-Cell Data Analysis: Process and analyze scRNA-seq datasets, including quality control, normalization, clustering, cell-type annotation, differential expression, and pathway analysis.
• Perturbation Data Analysis: Analyze cellular responses to chemical and biological perturbations, identifying changes in gene expression, cell states, and relevant biological pathways.
• Multimodal Data Analysis: Work with experimental scientists to combine transcriptomic results with drug-response measurements, high-content imaging features, and experimental metadata.
• Data Processing & Quality Control: Establish reproducible workflows for processing, organizing, and quality-checking biological datasets.
• Biological Interpretation: Translate computational findings into biologically meaningful insights and communicate results to experimental and AI research teams.
• Experimental Collaboration: Support experimental design by advising on sample selection, biological controls, data requirements, and analysis strategies.
• AI Research Support: Collaborate with AI scientists to prepare datasets for virtual-cell model training, evaluation, and benchmarking.
• Scientific Reporting: Prepare data visualizations, analysis reports, technical documentation, and scientific presentations.

Requirements & Qualifications

• Education: Bachelor's degree or above in Bioinformatics, Computational Biology, Bioengineering, Biological Sciences, Computer Science, or a related discipline.
• Experience: At least 3 years of relevant experience in bioinformatics, computational biology, or biological data analysis.
• Programming: Proficiency in Python and/or R for biological data processing, statistical analysis, and visualization.
• Single-Cell Analysis: Practical experience analyzing scRNA-seq data using established tools such as Scanpy, Seurat, or equivalent frameworks.
• Bioinformatics Knowledge: Good understanding of gene expression analysis, differential expression, clustering, and functional or pathway enrichment analysis.
• Biological Understanding: Basic knowledge of molecular and cellular biology, with the ability to interpret computational findings in a biological context.
• Data Analysis: Familiarity with statistical methods, data visualization, and reproducible computational workflows.
• Communication & Collaboration: Ability to work effectively with experimental scientists and computational researchers.

Nice to Have

• Experience analyzing drug-screening, perturbation, or cancer-related datasets.
• Familiarity with high-content imaging data or quantitative cellular phenotyping.
• Experience integrating multiple biological data types, such as transcriptomics and imaging.
• Familiarity with machine learning, deep learning, or single-cell foundation models.
• Experience with Linux, Git, or high-performance computing environments.

Ready to Build What's Next

We're not just designing machines – we're building the future of autonomous and intelligent science and manufacturing. Join Galatek and help bridge automated biological experimentation with computational analysis and AI-driven discovery.

Galatek is proud to be an equal opportunity employer. We celebrate different perspectives and believe diversity drives innovation. All employment decisions are made fairly, without regard to race, ethnicity, religion, gender, sexual orientation, age, disability, or any other characteristic that makes each individual unique.

For interested applicants, we welcome you to apply via the link / submit your updated resume to [Confidential Information] for consideration. We appreciate your interest and look forward to hearing from you. Please note that only shortlisted candidates will be contacted.