Our lab is made up of a highly engaged and collaborative team of scientists in the Perelman School of Medicine at the University of Pennsylvania dedicated to: 1) developing methods that analyze big data to understand complex biological systems and 2) putting these methods and big data into the hands of every biologist. Read through the appropriate heading below for information about joining the lab.

Programmer & Software Engineer Positions

Our programmers and software engineers are expected to contribute most of the code that goes into our production ready webservers and analytical pipelines. These professionals are expected to maintain high standards for code documentation, clarity, efficiency and maintainability. In addition to maintaining these standards in their own code, these members of the lab set high expectations for other lab members and share their expertise to improve the code that all members of the lab are writing. For the machine learning aspects of our work, we currently use a technology stack consisting of C/C++ (limited and decreasing), Python + numpy/scipy/scikit-learn/theano, and R with assorted packages. For the web development side of the lab, we currently use a technology stack of Postgres, Python (Django), and JavaScript (Angular.js and d3). Our data processing framework and webservers run on cloud instances, so experience with optimizing workloads for this type of environment is a plus. Feel free to contact Casey to be notified when job postings are available.

Postdoctoral Researchers

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.


Postdocs in our lab contribute to the development of new analytical methods and/or the application of these methods to new datasets. Postdocs will have the opportunity to work with large collections of genomic data, both publicly available and from collaborative projects, and to extract testable biological hypotheses from these large collections. Research projects center around new computational methods to integrate genomic data as well as to incorporate additional environmental and phenotypic information with these genomic data. Postdocs are expected to contribute to the lab's culture of open scientific discovery and to share methodological advances and biological discoveries at both national and international venues.


  1. 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.

  2. The ideal candidate will have a track record of scientific productivity and leadership and will strive for robust and reproducible analytical workflows.

  3. 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.

Pay and Benefits:

Postdoc positions in our lab start at a non-negotiable starting salary, which is currently $70,000 per year. These positions are considered Postdoctoral Trainee Appointments at Penn, which makes the postdoc eligible for an insurance plan and other benefits including a New Child Leave Policy. Additional information about Biomedical Postdoc Positions at Penn is available on the program website.


To apply, provide a CV, a short statement of research interests, and the names and contact information for three references through our application portal.

Graduate STudents

We welcome graduate students in Penn’s Genomics and Computational Biology (GCB) program. Our goal is to help our students to develop both a deep familiarity with the computational methods required for data-intensive science and a strong understanding of one or more biological application areas. We provide training in all aspects through group meetings, individual meetings, and a supportive lab environment. If you are interested in rotating in our lab, please e-mail Casey to set up a time to discuss your interest.

Undergraduate Students

We welcome undergraduate students into our lab, and undergraduate researchers have become first authors on papers submitted on research that they performed as part of our group. We are happy to train undergraduates in many aspects of data-intensive biology, and we have high expectations for their level of commitment to research. As an undergraduate, if you are interested in discussing research opportunities please e-mail Casey.