Forging ties between technologists and public policy experts, the Center for Information Technology Policy at Princeton University addresses societal issues, such as privacy and security, connected to advances in computer technology.
Center participants are from Princeton departments such as Computer Science, Economics, Electrical Engineering, Operations Research and Financial Engineering, and Sociology, and the Woodrow Wilson School of Public and International Affairs.
The Princeton Institute for Computational Science and Engineering (PICSciE) is an interdisciplinary institute designed to bring together faculty and researchers from diverse backgrounds leveraging their broad expertise to address new and relevant computational problems and thereby contribute to the body of scientific knowledge. Located in the Lewis Science Library on Washington Road and Ivy Lane, PICSciE provides state-of-the-art computing and visualization facilities in collaboration with the Office of Information Technology. Above all, PICSciE hopes to be of service to the faculty, postdoctoral fellows, and students doing computational research on campus.
Princeton University established the Center for Statistics and Machine Learning (CSML) in July 2014 to serve as the primary organization on campus for education and research activities in statistics, machine learning, and the data sciences. CSML will be an interdisciplinary group with research focused around methodological challenges at the intersection of these fields. CSML will also be deeply connected to real-world application areas, such as in astrophysics, economics, finance, genomics, neuroscience, political science, public policy, and sociology.
Understanding behavior at all levels of function, from systems to cells, is one of the great challenges of modern biology. At Princeton University, faculty with research interests in neuroscience can be found in many departments, including Applied Math, Chemistry, Computer Science, Engineering, Molecular Biology, Physics, Philosophy and Psychology. This diversity mirrors the interdisciplinary nature of contemporary neuroscience research and provides a rich set of opportunities for research and training in neuroscience. This web site provides information about the shared and individual interests of neuroscience faculty at Princeton, the opportunities available for training at the graduate and undergraduate levels, and neuroscience-related activities on campus.
The Program in Applied and Computational Mathematics (PACM) offers a select group of highly qualified students the opportunity to obtain a thorough knowledge of branches of mathematics indispensable for science and engineering applications, including numerical analysis and other computational methods. PACM runs a graduate program and an undergraduate certificate prog
The Program in Quantitative and Computational Biology (QCB), administered by the Lewis-Sigler Institute for Integrative Genomics, is intended to facilitate graduate education at Princeton at the interface of biology and the more quantitative sciences and computation. This is meant to include, among others, the fields of genomics, biophysics, computational neurobiology, systems biology, population biology and quantitative genetics, molecular evolution, computational biology and microbial interactions, all of which are already of interest to faculty in the collaborating departments and the Institute. Ph.D. degrees will be offered by the collaborating academic departments with some indication of the interdisciplinary nature of the thesis.