Sort by
Refine Your Search
-
on data science and engineering. The scientist will collaborate with Princeton and GFDL researchers to enhance, analyze and deliver high-resolution earth system model data, with an emphasis on Seamless
-
include: a Ph.D. in Neuroscience, Psychology, Cognitive Science, Computer Science, Engineering, or other related field, and strong experience with computational models, programming, and quantitative methods
-
quantitative and computational social science, addressing a diverse array of new data and analytic challenges, facilitating impactful multidisciplinary collaboration, scholarly advancement, and the creation
-
science, electrical and computer engineering, sociology, public policy, information science, communication, economics, political science, psychology, philosophy, and related technology disciplines. Selected candidates
-
collaborate with the ARG team on developing grant proposals. Qualifications Required qualifications: Doctoral degree in a related field, such as Computer Science, Robotics, Civil Engineering, Architecture, etc
-
develop and apply computational approaches for mass spectrometry data, with artificial intelligence/machine learning (AI/ML) being a major focus. They will have an opportunity to lead and contribute to a
-
interests in astrophysics at the Princeton Plasma Physics Lab and in the Physics, Geosciences, and Mechanical and Aerospace Engineering Departments, and at the nearby Institute for Advanced Study. The Term