Position Summary
The position is responsible for analyzing and interpreting data using advanced mathematical and computational models to support project-related research on the biomedical and behavioral dimensions of population dynamics for both communicable and non-communicable diseases.
Job Responsibilities
- Develops mathematical models describing disease dynamics and the impact of interventions.
- Formulates hypothesis independently and performs comprehensive data analysis using mathematical modeling across multiple research projects.
- Develops, validates, and maintains deterministic, stochastic compartmental, and individual-based models to support disease-related investigations.
- Partners with principal investigators and multidisciplinary research teams to co-develop study designs, and define robust computational plans aligned with research aims.
- Interprets modeling outcomes and prepares reports, visualizations, and scientific manuscripts summarizing findings and contributes to manuscripts and grant submissions.
- Writes and publishes articles in peer-reviewed journals that highlights research findings.
- Presents research results in internal meetings and external scientific conferences.
- Maintains accurate documentation of analytical methods, results, and project progress.
- Researches articles with respect to the assigned study, keeps up to date with the latest developments and identifies areas of improvement.
- Guides team members on the effective use of tools, methods and workflows as required.
- Performs other duties as assigned.
Skills
Education
Experience
Ph.D. in Mathematical Epidemiology, Applied Mathematics, Theoretical Physics, or a related quantitative discipline with relevant post-qualification experience.
Knowledge, Skills and Abilities
- Extensive knowledge of mathematical modeling frameworks, including deterministic and stochastic approaches.
- Extensive knowledge of quantitative methods including differential and integral equations, nonlinear dynamics, probability theory, and stochastic processes.
- Expert at scientific computing, including programming, numerical analysis, symbolic and logical analysis, Monte Carlo simulations, and computer graphics.
- Extensive knowledge in use of scientific computing tools such as MATLAB, Mathematica, and Berkeley Madonna, and statistical software including SPSS and R.
- Advanced problem-solving and analytical skills with an eye for detail.
- Excellent organizational skills with the ability to manage multiple priorities in demanding timeframes.
- Proficient in MS Office Suite (Word, Excel, PowerPoint, Outlook).