Research Assistant (Medicine Chronic Hepatitis B (CHB)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Assistant-%28Medicine-Chronic-Hepatitis-B-%28CHB%29/32334-en_GB/st=34E3EC5DC8E1058534E5F22E2A09700A887DA9A5

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Job Description

Chronic Hepatitis B (CHB) remains a major global health challenge, and functional cure, defined by HBsAg loss and immune restoration , is rarely achieved.

Our multidisciplinary program integrates clinical cohorts with mechanistic laboratory studies to uncover how hepatocytes transition from a pro-viral tolerant state to an immune-reactive flare state that precedes viral clearance.
This program is supported by longitudinal clinical datasets and paired liver biopsies, generating high-dimensional multi-omic data that require computational analysis to resolve intrahepatic immune and viral state transitions.

This research aims to identify molecular triggers and therapeutic targets that drive immune-mediated HBV flares, combining hepatocyte biology, RNA therapeutics, and spatial transcriptomics.

A major component of this work involves analysis of spatial transcriptomics and transcriptomic datasets to map cellular states, trajectories, and microenvironmental interactions associated with HBV flare and functional cure.

Key Responsibilities

Perform data analysis and computational workflows supporting the project.

Lead or support bioinformatics analyses including:

RNA-seq and spatial transcriptomics data processing
Dimensionality reduction (PCA, PHATE, diffusion maps)

Trajectory and state-transition analysis
Pathway and gene set enrichment analyses
Integration of clinical and molecular datasets

Work with existing pipelines (R/Python) and contribute to development of reproducible analysis workflows.

Maintain meticulous experimental records, data organization, and documentation.

Support data analysis and visualization (Excel, GraphPad, or Python/R if skilled).

Liaise with clinical teams and collaborators to integrate computational findings with clinical and translational aspects of the project.
Limited exposure to experimental workflows may be available if required.

Qualifications

Bachelor's degree in Life Sciences, Biomedical Sciences, or Molecular Biology.

Prior experience in data analysis, coding (R/Python), or bioinformatics is strongly preferred.

Experience with hepatocyte or viral systems (HBV, HCV, etc.) is an advantage.

Prior wet-lab experience (cell culture, molecular assays) is not required but may be considered an advantage.

Strong work ethic, curiosity, and ability to learn new techniques quickly.

Willingness to be trained in new computational and/or experimental techniques as required.

Excellent organizational, communication, and teamwork skills.

Training & Opportunities

Exposure to cutting-edge platforms: RNA therapeutics, AAV-HBV1.2 mouse models, and spatial transcriptomics (CosMx).

Hands-on training in bioinformatics workflows, including transcriptomic and spatial data analysis, using real clinical datasets.

Opportunity to contribute to high-impact publications and national translational HBV consortia.

Ideal stepping stone for candidates aiming for PhD training or biomedical research careers.