National University of Singapore | Research Associate
1 week ago
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
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