Research Fellow (Ref:DMSTBT)

The bioinformatician RF will be a key member of Professor Teh Bin Tean’s Laboratory of Cancer Epigenome at the National Cancer Centre Singapore, where the team conducts integrated epigenomic and genomic profiling of Asian cancer and aging samples using technologies such as ChIP-seq, RNA-seq, whole-genome sequencing, and DNA methylation sequencing. Working alongside other bioinformaticians, the successful candidate will contribute to a wide range of cancer epigenetics and genomics projects involving next-generation sequencing (NGS). Responsibilities include managing and analyzing NGS datasets, supporting experimental biologists, developing and implementing bioinformatics tools and computational workflows, and assisting in the preparation of research publications.

Your responsibilities will include:
- Human Genomic Analysis: Conduct in-depth genomic studies on human samples for cancer and aging studies to design therapeutics.
- Multi-Omics Integration: Combine data from genomics, proteomics, and metabolomics to gain comprehensive insights into human biology.
- NGS Data Analysis: Utilize advanced NGS techniques and tools for high-throughput data analysis.
- Research Publication: Lead, prepare and contribute to high-impact research publications.

Requirements:
- PhD in Bioinformatics, Genomics, Mathematics, Physics, or related fields.
- Work Experience: At least 1-year experience in NGS data analysis.
- Technical Skills: Familiarity in Unix-based OS and High-Performance Computing (HPC).
- Programming Skills: Competent in genomic data exploration, analysis, and visualization using any programming language, e.g., R, Python, or Perl.
- Multi-Omics Data: Experience in preprocessing and analyzing multi-omics sequencing data (DNA/RNA/ChIP-Seq) using state-of-the-art bioinformatics tools/software/pipelines.
- Project Management: Ability to manage and lead projects, either individually or as part of a team.
- Knowledge of cancer biology is a plus.
- Knowledge of statistical testing/analysis.
- Knowledge of developing predictive models, dimensionality reduction techniques.
- Knowledge of analysing single-cell omics data is a plus.
- Innovation and Initiative: Displaying a strong interest in cancer genetics. Demonstrated ability to generate innovative ideas and concepts to drive projects forward. 
- Interpersonal Skills: Strong team player with good interpersonal skills.
- Continuous Learning: Eagerness to take on new challenges and committed to continuous learning.