Bioinformatician (Cancer Science Institute, GeDac)

Bioinformatician (Cancer Science Institute, GeDac) University-Level Unit:

Cancer Science Institute of Singapore

Faculty/Department-Level Unit:

Research

Employee Category:

Research Staff

Location:

Kent Ridge Campus

Posted On:

06/11/2026

Job Description The Cancer Science Institute of Singapore (CSI) is seeking a collaborative and highly skilled Genomic Data Scientist/Bioinformatician to join our Genomics and Data Analytics Core (GeDaC). Our facility is powered by a

multi-disciplinary team of cloud engineering experts

who are establishing a

robust, petabyte-scale infrastructure

on AWS for the automated processing and analysis of large-scale cancer genomics datasets.

This role is specifically designed for a scientist who excels at

building state-of-the-art bioinformatics workflows for RNA-sequencing analyses . You will leverage our production-grade "AI Factory" to move beyond standard pipelines, exploring the intricate complexities of the transcriptome at a massive scale to advance biological discovery and precision medicine.

Key Responsibilities Working collaboratively with software engineering experts, principal investigators, and research teams, the successful candidate will:

Large-Scale Data Operations : Collaborate with a strong engineering team to design and optimize cloud-based components capable of processing and analyzing

genomic datasets spanning thousands of patients .

Intricate RNA Analysis : Lead advanced transcriptomic investigations, with a particular focus on

alternative splicing, transcript discovery, RNA editing, and RNA modifications .

Platform & API Development : Help design biologically-sensible APIs for genome analytics to be utilized by research teams.

Scientific Collaboration : Provide expert bioinformatics consultation to CSI/NUS investigators, communicating complex results clearly to diverse audiences.

Strategic Initiatives : Participate in state-of-the-art machine learning, AI, and big data projects driven by institutional and national initiatives.

Requirements Education & Experience

Master's or Ph.D. in Genetics, Genomics, Bioinformatics, Computational Biology, or Data Science.

Proven track record of processing and analyzing high-throughput sequencing data (NGS) at scale, with an emphasis on large-scale RNA-seq or single-cell cohorts.

Technical Skills

Programming Proficiency: Strong proficiency in Python and/or R.

Computational Infrastructure: Familiarity with High-Performance Computing (HPC) and/or cloud computing environments (AWS preferred).

Reproducibility: Understanding of version control systems (Git) and reproducible research practices.

Professional Attributes

Strong problem-solving abilities and the analytical thinking required to manage multi-thousand sample datasets.

Commitment to producing high-quality, reproducible work within collaborative, multidisciplinary teams.

Preferred Qualifications

Specialized RNA Expertise: Demonstrated experience in analyzing splicing, transcript discovery, RNA editing, or RNA modifications.

Workflow Mastery: Familiarity with workflow management systems such as Nextflow, Snakemake, or WDL.

Data Management: Understanding of database systems and data management practices.

Scientific Impact: Authorship on peer-reviewed scientific publications showcasing large-scale genomic analysis.