Oncology Data Scientist: Multi-Omics & Biomarker Analytics

Singapore National Eye Centre; Singapore; On-site; SGD 100,000 - 180,000; Full time

Job summary

National Cancer Centre Singapore Pte Ltd is seeking a Data Scientist (DMSMC) to join the Precision Radiotherapeutics and Oncology Programme and the Data and Computational Science Core. The role focuses on integrating EMR, NGS, radiology, and other multimodal data to develop biomarkers predicting clinical responses in cancer patients.

The candidate will work with PI and clinical teams to optimize data pipelines, perform ML/DL analyses, and contribute to translational research across multiple

Qualifications

• Postgraduate degree at least a master’s level in bioinformatics, quantitative or computational biology, data science, computer science, or related field.
• Experience analysing multi-omics data and clinical data using statistical methods, classical machine learning, deep learning, and language models.
• Proficiency in Python, R, or another relevant programming language.

Responsibilities

• Optimize genomic, transcriptomic, and radiomic data-processing and statistical-analysis pipelines.
• Perform feature engineering for statistical modelling, machine learning, and deep learning.
• Conduct survival analyses and other relevant computational analyses to understand cancer progression and treatment resistance across multiple cancer types.
• Contribute to and guide research discussions with scientists and clinical collaborators.

Skills

Data analysis

Statistical modelling

Machine learning

Deep learning

Survival analysis

Education

Masters in bioinformatics / computational biology / data science

Tools

Python

R

Shell (bash/zsh)

High-performance computing

Job description

National Cancer Centre Singapore Pte Ltd is seeking a Data Scientist (DMSMC) to join the Precision Radiotherapeutics and Oncology Programme and the Data and Computational Science Core. The role focuses on integrating EMR, NGS, radiology, and other multimodal data to develop biomarkers predicting clinical responses in cancer patients.

The candidate will work with PI and clinical teams to optimize data pipelines, perform ML/DL analyses, and contribute to translational research across multiple