"Research Fellow (OR/CBDS/RH)"

Job Title: Research Fellow (OR/CBDS/RH)

Posting Start Date: 16/12/2025

Job Description

The Laboratory of Cancer Ecosystems, led by Assistant Professor Regina Hoo, is seeking a Research Fellow / Senior Research Fellow to contribute to the lab’s efforts in understanding how diverse cell lineages co-evolve to shape cellular identity and tissue function in health and disease. We are an interdisciplinary team that integrates wet-lab and computational expertise to uncover principles of cancer initiation, progression, and therapeutic response or resistance.

The candidate will take the lead on computational and bioinformatic analyses, primarily supporting our translational research program, with the opportunity to collaborate with clinicians and broader research community within SingHealth and Academia campus.

• Analyse and interpret single-cell and spatial transcriptomics datasets to uncover cellular heterogeneity, functions and interactions from high-resolution mapping of cancer biospecimens.
• Design and implement computational pipelines, statistical and machine learning methods for data preprocessing, analysis and visualisation.
• Develop integrative approaches combining multi-omics, clinical, and public datasets to model disease conditions and predict outcomes.
• Manage and maintain databases of processed datasets for use by internal and external stakeholders.
• Participate and present in lab meetings, local and international conferences.
• Collaborate with internal and external wet-lab scientists to design experiments and validate computational predictions.
• Document and present results through manuscripts, publications, graphical visualizations, and presentations.
• Provide mentorship to junior members and assist in training students.
• Perform other related duties as required.

Job Requirements

• Ph.D. in Computational Biology, Computer Science, Bioinformatics or Genetics/Genomics.
• Candidates with background on cancer biology are preferred.
• Proven publication record in reputable journals.
• High competency with Python, R, bash, and deep learning frameworks including PyTorch and TensorFlow/Keras for modeling complex biological data.
• Experience with Linux and containerization tools (Docker/Singularity) in high performance computing environments.
• Excellent organizational skills and meticulous record-keeping.
• Proven ability to work effectively in a collaborative, multidisciplinary team.
• Strong critical thinking, communication, and presentation skills.
• Able to prioritize, multi-task, and work independently in a diverse research environment.

We regret that only shortlisted candidates will be notified.

More Information

Location: Outram Campus

Organization: Duke-NUS Medical School

Department: Office of Education

Employee Referral Eligible: No

Job requisition ID: 31239

Apply now