Bioinformatics Scientist - Single-Cell & Multimodal Data

Galatek Life Sciences; Singapore; On-site; SGD 120,000 - 170,000; Full time

Job summary

Galatek Life Sciences seeks a Bioinformatics Scientist – Single-Cell & Multimodal Data Analysis to support AI-driven biological research by analyzing data from automated cellular experiments. You will develop bioinformatics workflows for processing scRNA-seq, perturbation data, and quantitative cellular phenotypes.

A key focus is generating high-quality, well-annotated datasets to support virtual-cell research, where measurements are used to understand and predict cellular responses to

Qualifications

• Bachelor’s degree or higher in a related field.
• 3+ years of relevant experience in bioinformatics or computational biology.
• Proficiency in Python and/or R for data processing and visualization.

Responsibilities

• Process and analyze single-cell RNA-seq data, including QC, normalization, clustering, and differential expression.
• Analyze perturbation data and gene expression changes across conditions and pathways.
• Work on multimodal data integrating transcriptomics with imaging and drug-response data.
• Establish reproducible workflows for data processing, QC, and organization.
• Translate computational results into biological insights for experimental and AI teams.
• Collaborate on experimental design, sample selection, and data requirements.
• Prepare datasets for virtual-cell model training, evaluation, and benchmarking.
• Produce data visualizations, analysis reports, and scientific presentations.

Skills

Python/R programming

Single-cell data analysis

Data visualization & statistics

Communication & collaboration

Education

Bachelor’s degree or above in Bioinformatics, Computational Biology, Bioengineering, Biological Sciences, Computer Science, or a related discipline

Tools

Scanpy

Seurat

R

Python

Job description

Galatek Life Sciences seeks a Bioinformatics Scientist – Single-Cell & Multimodal Data Analysis to support AI-driven biological research by analyzing data from automated cellular experiments. You will develop bioinformatics workflows for processing scRNA-seq, perturbation data, and quantitative cellular phenotypes.

A key focus is generating high-quality, well-annotated datasets to support virtual-cell research, where measurements are used to understand and predict cellular responses to