Research Fellow (CBDS/CJM)

Duke-NUS Medical School; Singapore; On-site; SGD 70,000 - 100,000; Full time

Job summary

Duke-NUS Medical School's Centre for Biomedical Data Science (CBDS) invites applications for a Research Fellow to advance AI-powered analyses of single-cell and spatial omics. The successful candidate will join a collaborative team developing AI models for biomarker discovery and drug target identification at the Outram Campus in Singapore.

The role involves developing computational tools, performing large‑scale omics analyses, and contributing to manuscript preparation while mentoring junior

Qualifications

• PhD in a related scientific area with hands-on experience in bioinformatics and genetics/genomics data analyses.
• Familiar with handling and manipulating omics datasets including spatial transcriptomics, RNA-seq, and single-cell RNA-seq.
• Proficient in R/Python and Linux/Bash.
• Prior experience with additional computational platforms (e.g., Quantum computing, Perl, Java) preferred.
• Team player with ability to prioritize, multitask and collaborate in a diverse workforce.

Responsibilities

• Develop new computational tools applying AI/deep learning/machine learning/statistics to spatial and single-cell omics data.
• Independently conduct computational and bioinformatics analyses for large-scale omics studies.
• Interpret omics data, conceptualize ideas, and develop independent research plans in single-cell/spatial omics.
• Write and review research papers and present research outcomes.
• Perform data curation and data backups; contribute to project management and mentorship of junior researchers and students.

Skills

R

Python

Linux/Bash

Bioinformatics

Education

PhD in a related scientific area

Tools

Quantum computing

Perl

Java

Job description

Job Description

Dr Chen Jinmiao is looking for a motivated Research Fellow to join her laboratory within the Centre for Biomedical Data Science (CBDS). The successful candidate will contribute to AI-powered analyses of single-cell and spatial omics to advance precision medicine. Dr Chen’s research team develops AI algorithms for spatial and single-cell omics, integrates publicly available datasets into a centralised data hub, and leverages this platform to build AI models for biomarker discovery and drug target identification.

The selected candidate will perform a variety of research activities under the supervision of the Principal Investigator, including but not limited to the following:

• Develop new computational tools through the application of AI / deep learning / machine learning / statistics on spatial and single-cell omics (transcriptomics, proteomics, epigenomics, metabolomics, meta-transcriptomics, etc.) data.
• Independently carry out computational and bioinformatics analysis for large-scale spatial and single-cell omics as well as next generation sequencing studies.
• Application of qualitative and quantitative research techniques which include accurate in-depth assessment, interpretation, and evaluation of -omics data sets, conceptualise new ideas and develop plans for independent research in the field of single-cell and spatial omics and other -omics data modalities.
• Write and review research papers and present research outcomes.
• Perform routine duties related to the research study, such as data curation and making data backups, as required.
• Contribute to project management, provide guidance to junior researchers as well as undergraduate and graduate students, occasional educational/instructional activities.
• Perform other related duties incidental to the work described herein.

Job Requirements

• PhD in a related scientific area (e.g., AI, Deep Learning, Machine Learning, Statistics, Database, Bioinformatics, Computational Biology, Computer Science, Data Science, Data Analytics, Biology) with demonstrated hands on experience in bioinformatics and genetics/genomics data analyses.
• Familiar with and experienced in handling and manipulating omics datasets, including spatial transcriptomics, RNA-seq, and single-cell RNA‑seq, etc.
• Proficient in R / Python and Linux / Bash.
• Prior experience and working knowledge of additional computational platforms and applications (e.g. Quantum computing, Perl, Java, etc.) preferred.
• A team player who is able to prioritise, multi-task and work collaboratively in a diverse workforce.

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 : 34288