Research Fellow, Population and Global Health

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.

LKCMedicine is seeking a full-time Research Fellow in health informatics and epidemiology to join Professor John Chambers’ team for the SG100K study and the PRECISE-SG100K initiatives, to deliver high-quality SG100K research data to enable scientific discovery for bringing precision health for Singapore and beyond, in collaboration with our valued partners and stakeholders. The appointee will support the broader effort in, but not limited to, the SG100K study data curation, the integration of research phenotype data with EHR, phenotype derivations using large language models, disease endpoint coding initiatives, and creation of common data model (CDM). He/she will also be expected to support/lead high-quality research in chronic disease epidemiology and health informatics, that informs the development of effective public health interventions, including data analytics and manuscript preparation.

Key Responsibilities:
- Contributing to data curation, standardization, linkage with electronic health records, and quality assessment.- Developing and automating phenotype generation, endpoint coding and validation pipeline based on both observational data and electronic health records- Contributing to phenotype development based on high dimensional and free text data leveraging advanced methods such as large language models.- Analysis of epidemiological data from both observational population studies and data linkage to health records to understand chronic disease etiology.- Presenting at local, international conferences and workshops, using appropriate presentation formats.-
- Liaising with collaborators from local and international institutes, industry partners and government.- Critically reviewing the work of other members of the research team and mentoring less experienced members as necessary.

Competencies and Qualification Requirements:- Expertise in health informatics, particularly experience working with electronic health records (EHRs).- Experience of analyzing large-scale longitudinal population data.- Proficiency in programming languages such as Python or R.- Strong communication (oral and written) and interpersonal skills, and experience working in a large research group is desirable.- Fluent in spoken and written English.- Ability to work independently and collaboratively, with a proactive and motivated mindset, attention to detail.- Experiences of endpoint disease coding such as ICDs, SNOMEDs (desirable).- Experiences of OMOP Common Data Model (desirable).- Proficiency in Structured Query Language (SQL) (desirable).

Hiring Institution: LKC