Job Description

The Cancer Science Institute of Singapore is seeking a highly motivated Research Fellow (Bioinformatician) to join an interdisciplinary research team focused on cancer genomics, genome instability, and AI-driven computational biology. The successful candidate will develop and apply innovative computational methods to analyse large-scale multi-omic datasets, identify mutational patterns across cancer genomes, and build predictive models that improve our understanding of tumour evolution and therapeutic vulnerabilities.

This position offers an exciting opportunity to work at the interface of computational biology, artificial intelligence, statistical genomics and cancer research within a collaborative and internationally competitive research environment.

Key Responsibilities

Computational Genomics & Bioinformatics

• Develop, implement and optimise computational pipelines for analysing large-scale whole genome, whole exome and multi-omic sequencing datasets.
• Analyse somatic mutations across multiple mutational modalities, including:
  • Single Base Substitutions (SBS)
  • Insertions and Deletions (Indels)
  • Structural Variants (SVs)
  • Copy Number Alterations (CNAs)
  • Other genome instability features.
• Perform mutational signature analyses and investigate genome instability patterns across diverse cancer types.
• Integrate genomic, transcriptomic and clinical datasets to identify biologically meaningful associations.

Artificial Intelligence & Machine Learning

• Develop machine learning and AI models to identify, predict and characterise genome instability patterns.
• Design generative and predictive computational models to infer mutational processes under different biological conditions.
• Apply statistical learning, deep learning and probabilistic modelling approaches to large-scale cancer datasets.
• Evaluate and benchmark computational methods using publicly available and internally generated datasets.

Research & Scientific Discovery

• Investigate mechanisms underlying DNA damage, DNA repair deficiencies and cancer evolution through computational analyses.
• Collaborate with experimental researchers to validate computational predictions.
• Design reproducible computational workflows to support hypothesis generation and biological discovery.
• Contribute to the development of novel analytical methodologies for cancer genome analysis.

Scientific Communication

• Present research findings at laboratory meetings, scientific conferences and international workshops.
• Prepare manuscripts for publication in high-impact peer-reviewed journals.
• Contribute to grant applications and collaborative research proposals.
• Maintain accurate documentation of computational analyses and workflows.

Collaboration

• Work closely with computational scientists, cancer biologists, clinicians and AI researchers.
• Mentor junior researchers and graduate students where appropriate.
• Contribute to an open, collaborative and interdisciplinary research environment.

Qualifications

• PhD in Bioinformatics, Computational Biology, Computer Science, Statistics, Data Science, Genomics, Biomedical Engineering, Mathematics, or a related quantitative discipline.
• Strong publication record appropriate for career stage.
• Demonstrated experience in computational genomics or cancer bioinformatics research.
• Strong programming skills in Python and/or R.
• Experience working in Linux/Unix computing environments.
• Experience analysing high-throughput sequencing data (WGS, WES, RNA-seq and/or single-cell sequencing).
• Knowledge of cancer genomics, somatic mutation analysis and variant interpretation.
• Experience with statistical modelling and data analysis.
• Familiarity with version control systems (e.g. Git).
• Experience using high-performance computing (HPC) environments or cloud computing platforms.
• Excellent analytical, problem-solving and scientific communication skills.