Research Fellow - Singapore

Only for registered members Singapore

15 hours ago

$60,000 - $110,000 (SGD) per year *

* This salary range is an estimation made by beBee

Job Title: · Research Fellow (OR/CSCB/THW) · Posting Start Date: 26/01/2026 · Job Description · The laboratory of Dr. Tang Hong-Wen within the Signature Research Programme in Cancer and Stem Cell Biology (CSCB) at Duke-NUS is recruiting a Research Fellow with strong enthusiasm an ...

Job description

Job Title:
Research Fellow (OR/CSCB/THW)

Posting Start Date: 26/01/2026

Job Description

The laboratory of Dr.

Tang Hong-Wen within the Signature Research Programme in Cancer and Stem Cell Biology (CSCB) at Duke-NUS is recruiting a Research Fellow with strong enthusiasm and interest in muscle biology, aging, and cancer.

The Tang lab aims to understand how skeletal muscle function becomes impaired during aging and cancer, and how muscle-derived signals influence systemic disease.

Dr.

Tang's laboratory employs a unique cross-species and interdisciplinary approach, integrating Drosophila genetics, mouse models, human samples, and high-throughput sequencing to uncover evolutionarily conserved mechanisms underlying human muscle diseases.

A major focus of the lab is the analysis of bulk and single-cell transcriptomic datasets to dissect cellular heterogeneity, signaling pathways, and gene regulatory networks associated with muscle aging, sarcopenia, and cancer cachexia.

The Research Fellow will play a key role in driving computational and data-driven biomedical research, contributing to experimental design, integrative data analysis, and biological interpretation.

The position offers opportunities for independent research, mentorship, and high-impact academic publication in a highly collaborative research environment.

Independently carry out the design and execution of experimental research required by the research component of the project.
Perform comprehensive bioinformatics analyses of single-cell RNA-seq, bulk RNA-seq, and other high-dimensional omics datasets.

Design and implement analytical pipelines for data preprocessing, quality control, normalisation, clustering, differential expression, trajectory inference, and pathway enrichment analyses.

Integrate transcriptomic data across species, conditions, and experimental platforms.
Interpret complex datasets in close collaboration with experimental scientists to generate biologically meaningful hypotheses.

Write and review research papers, present research outcomes, conceptualise new ideas and develop plans for independent research which could have a considerable influence and impact on the relevant field attracting research funding.

Prepare figures, reports, oral presentations, and scientific manuscripts for publication.
Maintain accurate documentation of analysis workflows and optimal experiment progress in the laboratory to ensure reproducibility.
Provide guidance and mentorship to undergraduate / medical students and research assistants.
Perform other related duties incidental to the work described herein.

Job Requirements

PhD in Bioinformatics, Computational Biology, Life Sciences, Biomedical Science, or a related discipline.
Strong expertise in single-cell RNA-seq, bulk RNA-seq analysis, or other high-dimensional omics datasets.
Proficiency in R and/or Python, and familiarity with tools such as Seurat, Scanpy, DESeq2, edgeR, Monocle, or similar frameworks.
Experience working with large-scale sequencing datasets and high-performance computing environments.
Prior experience in muscle biology, aging, stem cell biology, or cancer research is advantageous but not mandatory.
Strong analytical thinking, problem-solving, and scientific writing skills.
Ability to work independently while collaborating effectively in an interdisciplinary and diverse research team.
Good organisational, time-management, and documentation skills.

We regret that only shortlisted candidates will be notified.

More Information

Location:
Outram Campus

Organization:
Duke-NUS Medical School

Department :
Office of Research

Employee Referral Eligible:
No

Job requisition

ID :
31479

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