Postdoc at Penn, working on methods for complex functional data with possible projects on hybrid FDA-ML/AI methods, distributional regression for wearable devices, and causal inference models incorporating functional data.
More information: Penn Morris Postdoc Ad 2024
Duties and Responsibilities: develop new methods for functional data analysis and its interface with biomedical and public health research; develop software; and potentially collaborate on applied projects in Biomedical, Public Health and Social Sciences.
Position Qualifications: Candidates should have a doctoral degree in biostatistics, statistics, or a related field. Strong computational skills in R/Python and expertise in one or more of the areas of functional data analysis, Bayesian modeling, deep learning, and/or causal inference are desired but not required. Start date and term are negotiable. An individualized development plan, mentoring, and travel support for at least two conferences per year will be provided as well as competitive salary and benefits.