Bioinformatics Engineer: RNA-Seq & Long-Read Pipelines

A*STAR RESEARCH ENTITIES; Singapore; Presencial; SGD 60.000 - 100.000; Jornada completa

Descripción de la vacante

Genome Institute of Singapore (GIS), a core lab within A*STAR, is seeking a Research Officer to support computational workflows and data processing. The role focuses on implementing and maintaining analysis pipelines, ensuring reproducible results, and collaborating across the lab to advance long-read transcriptomics and RNA modification detection.

The successful candidate will work closely with software engineers and biologists, applying Python-based tooling in a Linux environment, documenting

Formación

• Degree in CS, bioinformatics, or related field.
• Strong Python programming and clean code writing.
• Experience with Linux CLI and Git.
• Hands-on bioinformatics workflows experience.
• RNA-seq data analysis experience.
• Interest in bioinformatics and computational biology.
• Organised, detail-oriented, and collaborative.
• Ability to troubleshoot and document analyses.

Responsabilidades

• Run, maintain, and troubleshoot bioinformatics pipelines for RNA-seq and long-read sequencing data.
• Process, organise, and quality check sequencing datasets, and keep clear records of data and analyses.
• Implement, test, and document software tools and analysis scripts under the guidance of senior lab members.
• Support benchmarking of methods by preparing datasets, running comparisons, and summarising results.
• Maintain code, documentation, and computing resources so analyses are reproducible.
• Provide day-to-day computational support to lab members and collaborators.

Conocimientos

Python

Linux CLI

Git

Bioinformatics

RNA-seq analysis

Team player

Documentation

Educación

CS / Bioinformatics degree

Herramientas

Nextflow

Snakemake

Docker

Singularity

HPC clusters

Descripción del empleo

Genome Institute of Singapore (GIS), a core lab within A*STAR, is seeking a Research Officer to support computational workflows and data processing. The role focuses on implementing and maintaining analysis pipelines, ensuring reproducible results, and collaborating across the lab to advance long-read transcriptomics and RNA modification detection.

The successful candidate will work closely with software engineers and biologists, applying Python-based tooling in a Linux environment, documenting