Postdoctoral associate in population health sciences

Position SummaryThe 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 ResponsibilitiesDevelops 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.SkillsEducationPh DExperiencePh. D. in Mathematical Epidemiology, Applied Mathematics, Theoretical Physics, or a related quantitative discipline with relevant post‑qualification experience.Knowledge, Skills and AbilitiesExtensive 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, Power Point, Outlook).