Job description

We are looking for highly motivated and talented individual with passion in oncology and genomics research to join the Precision Radiation Oncology Program and the Data and Computational Science Core at the National Cancer Centre Singapore. You will primarily work with the Principal Investigator (PI) and the current research and clinical teams. The selected individual is expected to contribute actively to our genomics and radiomics research that is focused on using electronic medical records, next-generation sequencing (NGS) and radiological imaging datasets to developing biomarkers predictive of clinical responses in cancer patients. Specifically, the Research Fellow will be expected to perform genomics and radiomics data processing, statistical analyses, feature extraction for statistical/machine learning and survival analysis, and other relevant computational analyses to better understand the complexity of cancer progression and treatment resistance of head and neck and prostate cancers. You will also be required to guide research discussions with other scientists and mentor students. There will also be ample opportunities for inter-departmental and cross-institution collaborations with oncologists, pathologists, and scientists.

For more information, please feel free to refer to the laboratory website - www.chualabnccs.com.

Requirements

(Required)
  • PhD in Computational Biology or Computer Science or Mathematics or Biostatistics or Biophysics
  • Highly motivated, organised, meticulous and committed to high quality standards
  • Prior experience in handling data sets (e.g. data curation, cleaning and organisation)
  • Competency in python/R or other computing language
(Good to have)
  • Demonstrable data analysis skills with a portfolio on relevant datasets (e.g. TCGA, Kaggle)
  • Familiarity with command line shells (e.g. bash, zsh)
  • Prior experience working with high-performance computing clusters and job schedulers
  • Knowledge and experience in biostatistical analyses of clinical datasets
  • Knowledge and experience in genomics analyses (e.g. analyses of WES, RNASeq data)
  • Able to work independently under pressure as well as in a team
  • Strong organizational, interpersonal and presentation skills
  • Responsible, analytical and self-confident with a mature personality
  • Keen interest to solve clinical problems.

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