Associate Research Scientist

The Department of Epidemiology at the Mailman School of Public Health seeks a full-time Associate Research Scientist to work at the intersection of epidemiology and causal inference, contributing to several ongoing studies involving the prevention and treatment of opioid use disorder. Reporting to the Principal Investigator, the Associate Research Scientist will provide expertise to: i) oversee data management, ii) conduct analyses to contribute to the aforementioned ongoing projects, often using semiparametric estimation methods, iii) conduct simulations, iv) turn new statistical methodology into usable software, v) contribute to drafting manuscripts, and vi) provide mentorship/assistance to junior members of the group.

Methodologically, the ongoing projects involve a focus on heterogeneous effects and optimization through individualized optimal dynamic treatment regimes; a candidate with an interest in these areas of health is preferred. The successful candidate will have experience in both applied and theoretical research experience in non-parametric causal inference, with longitudinal data analysis, simulations, and expertise in R, including software development.

Essential Functions

Write software programs and develop algorithms for analyzing data - 45%

Analyze output from these programs and help draw conclusions from them. - 15%

Create presentations of results and supporting material for scholarly papers and proposals. 5%

Write and edit research manuscripts. 30%

Perform other related duties (e.g., mentoring) as assigned - 10%

Minimum Qualifications

A PhD in a quantitative field (e.g., epidemiology, mathematics, biostatistics/statistics, finance, economics, and engineering) and a minimum of 2 years of related experience. T

Additional Qualifications:

Experience with quantitative data management and analysis, including semi-parametric estimation approaches.

Experience working on a computing cluster for conducting simulations.

The ability to work with large teams of diverse investigators and collaborators.

Proficiency in R is essential.

Excellent written and oral communication skills and be detail oriented.

High-level interpersonal and organizational skills.

Preferred Qualifications

A PhD and a Master's degree in biostatistics, epidemiology, or statistics is preferred.

Software development in R.