Research Fellow (CBDS / CJM)

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.