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Postdoctoral Research Fellow

Company Information

The University of Pennsylvania (UPenn) provides an outstanding training environment for biomedical research. Penn School of Medicine is an internationally recognized leader in the creation of new knowledge and one of the finest medical schools in the United States, in which it is consistently at the forefront of new developments and innovations in the biomedical research. There are countless collaborations among faculty from different departments at UPenn to conduct research through resource sharing and interdisciplinary communication. In addition to inner campus collaboration, UPenn has central ties with other frontier institutes, which include but are not limited to Children’s Hospital of Philadelphia and National Institutes of Health (NIH). This situation allows postdoctoral research fellows to easily take advantage and build an academic network for their long-term career goal.

Duties and Responsibilities

The postdoctoral research fellow will work on two funded projects. In a NIH funded project, the fellow will work with the advisor and clinical collaborators at the Children’s Hospital of Philadelphia to develop statistical tools to monitor disease dynamics using functional data analysis of multivariate longitudinal clinical data. Methods will be developed to address informative sampling and measurement errors in medical records. In a PCORI project, the fellow will work with the mentor and a co-PI at the University of Pennsylvania to develop statistical tools to integrate data from multiple hospitals. The fellow is expected to lead multiple 2-3 research projects, develop methods and software pipelines, perform data analysis, and contribute to manuscripts. The fellow will work in a team environment, under the supervision of Dr. Jing Huang.

The fellow will have opportunities to collaborate in multiple applied projects. For example: prediction of post surgery complication and patient profiling using machine learning approaches to support integrated, patient-centered intervention.

Position Qualifications

Required: doctoral degree in Biostatistics, Statistics, Bioinformatics, Computer Science or a related field.

Preferred:
Strong theoretical training in statistics and computing (R, python, C++).
Strong communication skills and experience of writing scientific papers.
Experience in statistical theory and methods development, machine learning, and comparative effectiveness research is preferred.
The positions are available immediately and for up to three years.