Visiting Research Fellow

Job Description

The Visiting Research Fellow will join Dr Chen Jinmiao’s research team at the Centre for Computational Biology (CCB), where they develop AI algorithms for spatial and single-cell omics. The role involves integrating publicly available data into a centralised hub and using 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.
• Application of qualitative and quantitative research techniques which include accurate in-depth assessment, interpretation, and evaluation of -omics data sets, conceptualize 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.