The Department of Epidemiology at Columbia University Mailman School of Public Health in New York City invites applications for a Postdoctoral Research Scientist with interest in dynamic modeling and statistical inference, with applications to infectious diseases and potentially cancer diseases. The fellow will join an experienced modeling team to develop cutting-edge model Bayesian inference systems for a project to study the spatial, temporal, and demographic dynamics of measles epidemics in recent decades and test different intervention/elimination strategies. Depending on his/her research interest, there are also opportunities to participate in other ongoing research projects; these include 1) study of SARS-CoV-2 transmission dynamics; and 2) study of risk factors contributing the recent increases in young onset cancers. For more details of the research team, see https://blogs.cuit.columbia.edu/wy2202/

The fellow is expected to increase his/her methodological and substantive knowledge of one or more of the aforementioned areas, build skills for developing and implementing research studies, and have opportunities to lead and/or co-author manuscript publications. S/he will perform population health research activities, including processing large datasets, performing statistical analyses, developing dynamic models, programing to build and implement model-inference systems, preparing manuscripts for submission to peer-reviewed journals, delivering presentations at scientific meetings, and providing other research and methodological support for existing and ongoing studies.

The position offers up to two years of postdoctoral fellowship with compensation commensurate with experience, excellent benefits package and funds for travel to professional conferences and meetings. Individuals with the following characteristics will be competitive for the position: strong motivation and commitment to a career in disease modeling, excellent communication and quantitative skills, ability to conduct self-directed and collaborative research.

Qualifications:

• PhD, ScD, or equivalent degree in Applied Mathematics, Applied Statistics, Computational Biology, Epidemiology, Engineering or related analytical disciplines;
• Comprehensive understanding of statistical concepts and methods;
• Proficiency in at least one programing language (e.g., R, Python, Matlab);
• Excellent communication skills (both oral and writing), and analytical skills;
• Experience in mathematical modeling of high dimensional systems and/or agent-based modeling would be a plus.