| Full Description |
Responsibilities:
Develop and implement statistical models for the integration of RCT and observational data.
Contribute to the development of software packages for the simulation of mixed-type clinical data and methodological implementation.
Analyze longitudinal data to estimate time-varying treatment effects.
Collaborate closely with a multidisciplinary team of statisticians, clinicians, and data scientists.
Publish findings in peer-reviewed journals and present at relevant conferences. |
| Application Details |
Qualifications:
Ph.D. in Biostatistics, Statistics, Data Science, or a related field,
demonstrated computational skills and ability to code in one or more scientific programming languages (e.g., R, Python, etc),
experience with machine learning, causal inference, and longitudinal data analysis.
Successful candidates will have:
strong research interest in causal inference and machine learning,
demonstrated ability to lead statistical methodology research,
demonstrated ability to write scientific research papers with substantive applications (publication record in peer-reviewed journals is advantageous),
ability to work proficiently within deadlines in a collaborative environment and
excellent written and verbal communication skills.
Salary and Benefits:
Opportunity to work on a high-impact research project with leading experts in the field.
Access to rich datasets and state-of-the-art computational resources.
Competitive salary and benefits package.
Support for professional development and career advancement.
All interested applicants should email a CV/Biosketch and Cover Letter to amir.asiaeetaheri@vumc.org.
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