Research Fellow/ Senior Research Fellow, Risk Prediction
6 days ago
The Lee Kong Chian School of Medicine (LKCMedicine) trains doctors who put patients at the centre of their exemplary care. The School, which offers both undergraduate and graduate programmes, is named after local philanthropist Tan Sri Dato Lee Kong Chian. Established in 2010 by Nanyang Technological University, Singapore, in partnership with Imperial College London, LKCMedicine aims to be a model for innovative medical education and a centre for transformative research. The School's primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised for the quality of its medical expertise, facilities and teaching. The School is transitioning to an NTU medical school ahead of the 2028 successful conclusion of the NTU-Imperial partnership to set up a Joint Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in healthcare, with an expanded scope in the medical humanities. Graduates from the five-year undergraduate medical degree programme will have a strong understanding of the scientific basis of medicine, with an emphasis on technology, data science and the humanities.
We are seeking highly motivated individuals with a strong interest in cancer genetics and genomic medicine to join the research team under Associate Professor Joanne Ngeow. The Research Fellow/ Senior Research Fellow will play a key role in analyzing large-scale genomic and clinical datasets to uncover genetic factors contributing to cancer predisposition and to develop accurate cancer risk prediction models. This role involves developing computational pipelines, conducting statistical and bioinformatics analyses, and integrating multi-omics data to support precision oncology research. The position aligns with the University's mission to advance scientific discovery in cancer genetics and improve patient outcomes through genomic medicine.
Key Responsibilities:
- Integrate and analyze large-scale multi-omics datasets (genomics, transcriptomics, epigenomics) to derive biological insights
- Apply statistical and machine learning models to identify cancer risk biomarkers
- Integrate clinical, environmental, and lifestyle data to create predictive risk models
- Develop and implement computational pipelines for analyzing next-generation sequencing (NGS) data (whole genome, exome, RNA-seq).
- Work closely with clinicians, geneticists, and wet-lab researchers to interpret findings
- Contribute to scientific publications, presentations, and grant applications
- Ensure proper handling, storage, and security of genomic and clinical data. Adhere to ethical, regulatory, and institutional guidelines for genetic data analysis
Key Competencies and Requirements:
- PhD degree in Computational Biology, Bioinformatics, or a related field
- At least 2 years of experience in analyzing large-scale genomics datasets. Experience with NGS pipelines and multi-omics integration
- Familiarity with cancer genomics and functional interpretation of genetic variants
- Proficiency in Python, R, or other bioinformatics languages
- Knowledge of cloud computing, and high-performance computing (HPC) environments
- Strong ability to present findings and collaborate across disciplines
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