Job Description

Overview

Dr. Mark Muthiah’s Metabolic Liver Disease Research Lab at the National University of Singapore (NUS) is seeking smart, motivated bioinformatics and data analytics researchers to support computational and translational research in metabolic liver diseases. This role is primarily computational and data-driven, focusing on the analysis and integration of large-scale multi-omics and clinical datasets.

The successful candidate will have strong mathematical intuition, solid programming skills, and an interest in biological and biomedical data analysis. The position offers close mentorship, intensive research training, and strong consideration for PhD enrolment at NUS for outstanding candidates.

Key Responsibilities

• Perform bioinformatics analyses of high-throughput datasets including bulk RNA-seq, single-cell and spatial transcriptomics, WGS/WES, and GWAS
• Design and implement reproducible bioinformatics pipelines and workflows
• Apply statistical and computational methods to analyse omics and clinical datasets
• Integrate multi-omics and clinical data to generate biologically meaningful insights
• Conduct data quality checks and ensure data integrity
• Generate publication-quality figures and analytical reports
• Collaborate closely with biologists, pathologists, clinicians, and hepatologists

Qualifications

• Bachelor’s or Master’s degree (or near completion) in Bioinformatics, Computational Biology, Computer Science, Data Science, or a related field
• Proficiency in R and Python for bioinformatics analysis, statistical modelling, and visualization
• Strong hands-on experience with omics data analysis, with expertise in several (if not all) of the following: bulk RNA-seq, single-cell transcriptomics, spatial transcriptomics, WGS/WES, and GWAS
• Solid understanding of biostatistical methods, including linear, logistic, and Cox regression, correlation analysis, and clustering
• Experience working in Linux/Unix environments
• Strong analytical skills, attention to detail, and ability to independently analyse and interpret complex datasets
• Ability to communicate findings clearly and work effectively in a collaborative, multidisciplinary research environment

Preferred Qualifications

• Experience or strong interest in machine learning and AI, including XGBoost, CatBoost, CNNs, object detection, and image segmentation
• Experience working with clinical tabular datasets and integrating clinical and omics data
• Willingness to learn clinical concepts and biomedical context
• Experience with reproducible research practices, workflow management, or version control
• Knowledge of metabolism, liver biology, or translational biomedical research
• Experience with large datasets, databases, or SQL
• Prior research outputs (e.g., thesis work, preprints, or publications)

More Information

Location: Kent Ridge Campus

Organization: Yong Loo Lin School of Medicine

Department : Medicine

Employee Referral Eligible: No

Job requisition ID : 31754