The junior data scientist will join the Precision Radiotherapeutics and Oncology Programme (PROP). The scope of the projects conducted under the premise of PROP includes 1) early- and late-phase clinical trials; 2) cancer genomics and data science; and 3) translational cancer and radiation biology. For this role, the selected individual will be mainly working with the Principal Investigator (PI) and the research team under Theme 2.
Theme 2 projects involve studying cancer genomics of two main cancers, nasopharyngeal and prostate cancer. The data scientist will be required to analyse next generation sequencing (NGS) datasets, such as whole transcriptome sequencing, whole exome sequencing and/or panel sequencing data. He/she will also be involved in inter-departmental and cross-institution collaborations. He/she will be required to relate his/her data findings with clinical and biological insights, and effectively visualise and communicate his/her results to non-data science stakeholders, including oncologists, pathologists, and scientists. Initial training on existing analysis pipelines will be provided, following which the selected individual will be expected to continue to proactively learn and manage assigned research projects independently.
Requirements:
(Required)
- Degree in Computational Biology or Computer Science or Mathematics or Biostatistics or Biophysics or related.
- Independent, meticulous worker with strong initiative and good communications skills.
- Highly motivated with strong interest in research and computational biology.
- Competency in R is mandatory.
(Good to have)
- Prior experience in computational biology, bioinformatics and/or data science preferred.
- Prior experience in handling large data sets (e.g. data curation, cleaning and organisation) preferred.
- Knowledge and experience in biostatistical analyses of clinical datasets preferred.
- Knowledge and experience in genomics analyses (e.g. analyses of WES, RNASeq data) preferred.
- Familiarity with command line shells (e.g. bash, zsh) preferred.
- Demonstrable data analysis skills with a portfolio on relevant datasets (e.g. TCGA, Kaggle) preferred.
