
Senior Research Fellow
1 week ago
**Responsibilities**:
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
**Type of Employment**: Full-Time
**Minimum Experience**: 1 Year
**Work Location**: NUS
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