Research Associate (CCB/CJM)

Job Description

Dr Chen Jinmiao is looking for a motivated Research Associate to join the Centre for Computational Biology (CCB) who will participate in AI-powered analysis of single-cell and spatial omics for precision medicine. Dr Chen’s research team develop AI algorithms for spatial and single-cell omics, integrates publicly available data into a centralised hub, and utilises this platform to build AI models for discovering biomarker and drug targets.

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.
• Assist researchers in programming and data analysis.
• Perform analysis of complex and large-scale genomics data, including (but not limited to) WGS and transcriptomic data (including single-cell RNA-seq and spatial transcriptomics data).
• Use computational tools and algorithms written in one/all R, PERL and Python.
• Contribute to project management, presentations and publications of research work.
• Provide technical support and establish work procedures to ongoing research projects.
• Perform other related duties incidental to the work described herein.

Job Requirements

• Master’s Degree 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.
• Familiar with high-performance computing (HPC) environment and possesses good computational biology skills (experience in R, Perl, Python, SQL, Bash etc).
• 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 : 25537