An exciting opportunity has risen for a highly motivated Senior Research Fellow to join the Singapore Institute for Clinical Sciences (SICS) to work with a collaborative and multidisciplinary team for the project “Completing the Picture: Strengthening Fathers" Roles in Early Child Health and Neurodevelopment Through Targeted Interventions”. The SRF will be responsible for leading data-intensive quantitative research on the interactions between familial environmental, focusing strongly on comparing paternal factors with maternal and other household member factors, and the broader environment (e.g. built and natural environment) on child health, well-being, and development. The SRF will utilize skills in big data management, especially harmonizing and linking geospatiotemporal data with longitudinal cohort data, as well as quantitative causal inference and quasi-experimental techniques, to produce new scientific knowledge, write manuscripts, create presentations and reports, and brief collaborators and other stakeholders (academic, government, community, industry, etc.) as needed.
Job Responsibilities:
The successful candidate will be expected to engage in the following:
- Big data (geospatialtemoporal, multi-modal longitudinal cohort) management, processing, and analysis from a variety of sources (academic, government)
- Conduct quantitative causal inference analyses, e.g. quasi-experimental, instrumental variable, fixed-effects, difference-in-difference, etc.
- Where appropriate, conduct or advise on economic considerations in research, practice, or policy (e.g. program evaluation, cost-benefit analyses)
- Proactively seek out obtain, or develop new data sources that will support or expand the research
- Prepare reports and presentations for internal and external stakeholders
- Leading communications with internal and external project stakeholders, including coordinating and conducting briefings
- Write manuscripts for publication in high-impact journals
- Work closely with the PI and research team while showing a high degree of autonomy and proactiveness
Job Requirements
- Qualification & Field of Study: PhD in relevant quantitatively-focused discipline (e.g., Biostatistics, Economics with focus on Econometrics and causal inference methods).
- Min. Years of Experience: 3 years
- Other Requirements (e.g. Skills, Competencies):
- Experience and expertise in joining geospatialtemoporal data to longitudinal cohort data and harmonizing data across cohorts for the purposes of data analysis
- Experience and expertise obtaining, constructing, or developing measures and indicators of built and natural environment, human behavior (movement/migration), and other areal characteristics
- Strong quantitative skills, particularly in causal inference
- Strong knowledge of statistical programming in Python and/or R
- Strong skills in data management and workflow documentation and commitment to open and reproduceable research
- Evidence of peer-reviewed publications and conference papers in line with career stage
- Well-organized with strong attention to detail
- A team player with an ability to work independently
- Self-motivated in striving for the most rigorous science
Contact
For more information about the position, potential applicants are encouraged to contact Dr. Keri McCrickerd ([email protected]) directly with any questions.
