The Greene lab welcomes applications for computational postdoctoral positions at the University of Pennsylvania Perelman School of Medicine. The Greene lab's overarching goal is to transform how we understand complex biological systems by developing and applying computational algorithms that effectively model processes by integrating multiple types of big data from diverse experiments. Our goal is to then put these algorithms into the hands of biologists, through the development of usable webservers, the dissemination of successful applications, and the distribution of open source software.
Candidates are expected to have an MD, PhD, or equivalent, with a strong background in computer science, machine learning, statistics, genetics, bioinformatics, or closely related field and programming experience with attributable contributions to source code.
The ideal candidate will have a track record of scientific productivity and leadership and will strive for robust and reproducible analytical workflows.
The ideal candidate will have experience handling large datasets in a UNIX/LINUX environment, experience with high performance cluster or cloud computing, and a knowledge of existing software packages used for machine learning.