Deskripsi Pekerjaan
Join Singapore General Hospital (SGH), the nation's largest acute tertiary hospital and a globally recognized center of excellence in clinical care, research, and education. We are seeking a highly skilled and motivated Senior Bioinformatician to join our Molecular Laboratory team. In this pivotal role, you will leverage cutting-edge genomic technologies to drive precision medicine initiatives and enhance patient diagnostic outcomes.
As a key member of our laboratory science division, you will be responsible for the end-to-end management of high-throughput sequencing data. You will work in a collaborative environment alongside clinicians, pathologists, and laboratory scientists to interpret complex biological data, develop robust analytical pipelines, and support translational research projects. This is a unique opportunity to contribute to one of the world's leading medical institutions and help shape the future of healthcare through computational biology.
Tanggung Jawab
- Develop, optimize, and maintain automated bioinformatics pipelines for NGS (Next-Generation Sequencing) data analysis.
- Provide expert interpretation of genomic and transcriptomic data to support clinical diagnosis and research investigations.
- Collaborate with molecular pathologists to validate and implement new diagnostic assays within the laboratory.
- Manage large-scale genomic datasets, ensuring data integrity, security, and compliance with hospital privacy standards.
- Develop custom scripts and algorithms to streamline data processing and visualization for clinical reporting.
- Lead and mentor junior staff in bioinformatics best practices and technical workflows.
- Maintain current knowledge of evolving bioinformatics tools, public databases, and clinical literature.
Kualifikasi
- Master’s degree or PhD in Bioinformatics, Computational Biology, Computer Science, or a related field.
- Minimum 3-5 years of experience in clinical bioinformatics or a high-throughput molecular laboratory setting.
- Proficiency in programming languages such as Python, R, or Perl for biological data analysis.
- Extensive experience with Linux/Unix environments and high-performance computing (HPC) clusters.
- Strong background in NGS data analysis tools (e.g., GATK, BWA, SAMtools, Bedtools).
- Proven ability to interpret complex genomic variants and familiarity with databases like ClinVar, gnomAD, and OMIM.
- Excellent communication skills with the ability to translate complex data findings into actionable clinical insights.