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Open nowPosted 10 days ago

Research Fellow (CBDS/FQ)

MyCareersFuture94,028 open roles

Pay
SGD 5,500 – SGD 9,000 a month
Where
West, Singapore
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Your applicationOpen nowResearch Fellow (CBDS/FQ)MyCareersFuture · West, Singapore

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This job: posted 10 days ago

The posting

Job Description The Duke-NUS Centre for Biomedical Data Science (CBDS) serves as a central hub for Duke-NUS faculty specialising in Biostatistics, Bioinformatics, Systems Biology, Artificial Intelligence (AI), and other quantitative and data-driven sciences. CBDS functions as a strategic platform for cutting-edge research, education, and services in data science, AI, and biomedical computation, building on existing institutional initiatives such as DAISI. We are seeking a highly motivated and talented Research Fellow to contribute to integrative genomics and multimodal biological data analysis, with applications in ocular disease and other complex diseases. This is a unique opportunity to contribute to high-impact science in a world-class academic medical centre, in collaboration with SingHealth —Singapore’s largest healthcare network. The successful candidate will participate in diverse research projects under the supervision of Dr. Qiao FAN.

Responsibilities

  • Develop advanced statistical and machine learning modeling to conduct data analyses for large-scale multimodal (genomics, omics etc) studies.
  • Conceptualise new ideas, lead data-driven discoveries, ensuring in-depth assessment and interpretation of results.
  • Conduct efficient data analyses on large-scale clinical and biobank data, including (but not limited to) whole-exome sequencing and omics data.
  • Write high-quality research papers, present research findings, and foster collaboration with local and international researchers.
  • Assist in grant writing and reports for ongoing funded projects.
  • Mentor graduate students and junior researchers in a dynamic environment.
  • Perform other related duties incidental to the work described therein.

Job Requirements

  • PhD in Biostatistics, Computational Biology, Bioinformatics, Genetic Epidemiology, or a related field.
  • Strong experience in statistical modelling, machine learning/deep learning, genomics and multimodal biological, and biobank data analysis.
  • Proficiency in R, Python, Perl, and Linux environments.
  • A track record of first-author publication in reputable journals.
  • Strong writing and critical thinking skills, as well as good communication and presentation skills.
  • A team player who is able to prioritise, multi-task and work collaboratively in a diverse workforce.

Applicants who are interested should submit their CV, cover letter, and contact details for three referees.

We regret that only shortlisted candidates will be notified.

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