Natural Sciences

Statistics and Machine Learning

Research across the disciplines increasingly requires the integration of data science, statistics and machine learning to make cutting-edge advancements. Princeton University is dedicated to playing a vital role in preparing students to lead in these areas, and the Center for Statistics and Machine Learning (CSML) is a campus focal point for fulfilling this commitment.

Science, Technology, and Environmental Policy (STEP)

Princeton University's Program in Science, Technology and Environmental Policy (STEP) is based in the Woodrow Wilson School of Public and International Affairs with strong ties to the Princeton Environmental Institute. Many aspects of science and technology policy debates have been tackled with the tools of political and economic analysis that are the traditional strong suits of the Woodrow Wilson School.

Environmental Studies

While PEI has a graduate program, it does not offer graduate degrees.  Students interested in pursuing a graduate degree at Princeton University must apply for admission to a graduate degree-granting department or program by completing the electronic application form provided on the Graduate School website.  PEI can be listed as the interdepartmental program of choice.

The goal of PEI’s graduate program is to provide opportunities for doctoral students to explore environmental topics from an interdisciplinary perspective.  The Institute offers several opportunities including:

Materials Science

Through our courses and research opportunities, PRISM strives to give students a deep understanding of fundamental science and a great appreciation for technology development. Both undergraduate and graduate students alike are well-prepared for a wide variety of future career opportunities.

Students must apply to and be admitted to a specific academic department (not PRISM) and must fulfill all departmental and joint degree requirements, including a doctoral thesis related to materials.

Quantitative and Computational Biology

The Program in Quantitative and Computational Biology (QCB) is intended to facilitate graduate education at Princeton at the interface of biology, the more quantitative sciences, and computation. Administered from The Lewis-Sigler Institute for Integrative Genomics, QCB is a collaboration in multidisciplinary graduate education among faculty in the Institute and the Departments of Chemistry, Chemical and Biological Engineering, Computer Science, Ecology and Evolutionary Biology, Molecular Biology, and Physics.


How do our brains work? How do millions of individual neurons work together to give rise to behavior at the level of a whole organism? Training researchers to answer these fundamental, unanswered questions is the goal of the Ph.D. program in Princeton's Neuroscience Institute. Students in this program learn to use the latest techniques and approaches in neuroscience. Most importantly, students are trained in how to think, and how to develop new techniques and approaches. Creativity and originality are essential to cracking the puzzle of the brain.


The Department of Geosciences, together with its affiliated interdepartmental programs and institutes, serves as Princeton’s central focus for the earth, atmospheric, oceanographic and environmental sciences. As such, the department encompasses a rich diversity of scientific expertise and initiatives,  ranging from the measurement and modeling of global climatic change to high-pressure mineral physics, and from seismic tomographic imaging of the mantle to biogeochemistry and isotope geochemistry of the Earth and oceans.


The Department of Mathematics graduate program has minimal requirements and maximal research and educational opportunities. It differentiates itself from other top mathematics institutions in the U.S. in that the curriculum emphasizes, from the start, independent research. Each year, we have extremely motivated and talented students among our new Ph.D. candidates who, we are proud to say, will become the next generation of leading researchers in their fields. While we urge independent work and research, there exists a real sense of camaraderie among our graduate students.


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