Research Fellow (CBDS/FQ)

NATIONAL UNIVERSITY OF SINGAPORE; Singapore; Presencial; SGD 70 000 - 110 000; Tempo integral

Resumo da oferta

The Duke-NUS Centre for Biomedical Data Science (CBDS) at the National University of Singapore seeks a Research Fellow to advance integrative genomics and multimodal data analyses for ocular and complex diseases. The role involves developing advanced statistical and ML models, data interpretation, and collaboration with SingHealth researchers.

Requirements include a PhD in a quantitative field, strong publication record, and proficiency in R, Python, Perl, and Linux.

Qualificações

• PhD in Biostatistics, Computational Biology, Bioinformatics, Genetic Epidemiology, or related field.
• Strong experience in statistical modelling, machine learning/deep learning, genomics and multimodal data analysis.
• Proficiency in R, Python, Perl, and Linux environments.
• Track record of first-author publications in reputable journals.
• Strong writing, communication, and presentation skills; able to work in a diverse team.

Responsabilidades

• Develop advanced statistical and machine learning modeling for large-scale multimodal studies.
• Conceptualise ideas, lead data-driven discoveries, interpret results.
• Analyze large-scale clinical and biobank data (e.g., whole-exome sequencing, omics).
• Write research papers, present findings, and foster collaborations.
• Assist in grant writing and reports; mentor graduate students and junior researchers.
• Perform other duties related to the project.

Conhecimentos

Statistical modelling

Machine learning / deep learning

Genomics data analysis

Multimodal data analysis

Biobank data analysis

R

Python

Perl

Linux

First-author publications

Writing & communication

Team collaboration

Formação académica

PhD in Biostatistics, Computational Biology, Bioinformatics, Genetic Epidemiology, or related field

Ferramentas

R

Python

Perl

Linux

Descrição da oferta de emprego

Job Description

The Duke-NUS Centre for Biomedical Data Science (CBDS) serves as a central hub for Duke-NUS faculty specializing 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.

We regret that only shortlisted candidates will be notified.