RNA-Seq Genomics Data Scientist (Cloud & AI)

National University of Singapore; Singapore; On-site; SGD 110,000 - 170,000; Full time

Job summary

Cancer Science Institute of Singapore (CSI) at National University of Singapore seeks a Genomic Data Scientist/Bioinformatician to build state-of-the-art RNA-sequencing workflows and run large-scale analyses on cloud infrastructure. You will collaborate with software engineers and researchers to push transcriptome discovery and precision medicine initiatives.

Ideal candidates have advanced degrees and a strong track record with HPC or AWS-based pipelines, plus proficiency in Python or R and

Qualifications

• Master’s or Ph.D. in Genetics, Genomics, Bioinformatics, Computational Biology, or Data Science.
• Proven track record handling high-throughput sequencing data (NGS) at scale, including RNA-seq or single-cell cohorts.
• Strong programming skills in Python and/or R.
• Experience with HPC or cloud environments (AWS preferred).
• Familiarity with version control and reproducible research practices.

Responsibilities

• Collaborate with software engineering and research teams to design cloud-based data processing components for genomic datasets.
• Lead advanced RNA-seq analyses focusing on splicing, transcript discovery, RNA editing, and modifications.
• Develop and document genome analytics APIs for research use.
• Provide bioinformatics consultation to CSI/NUS investigators and communicate results clearly.
• Participate in ML/AI and big data initiatives driven by institutional programs.

Skills

Python

R

HPC

Cloud computing

Git

Workflow systems

Education

Master’s or PhD in Genetics, Genomics, Bioinformatics, Computational Biology, or Data Science

Tools

Nextflow

Snakemake

WDL

Job description

Cancer Science Institute of Singapore (CSI) at National University of Singapore seeks a Genomic Data Scientist/Bioinformatician to build state-of-the-art RNA-sequencing workflows and run large-scale analyses on cloud infrastructure. You will collaborate with software engineers and researchers to push transcriptome discovery and precision medicine initiatives.

Ideal candidates have advanced degrees and a strong track record with HPC or AWS-based pipelines, plus proficiency in Python or R and