[robotics-worldwide] [jobs] postdoc position at Rutgers University on foundations of intelligent machines
DIMACS, based at Rutgers University, invites applications for a postdoc interested in computational, mathematical or statistical foundations of intelligent machines. The postdoc position is available as part of a new NSF TRIPODS institute called DATA-INSPIRE.
DATA-INSPIRE is a new transdisciplinary (TRIPODS) Institute based at DIMACS and focuses on "Data Science for INtelligent Systems and People Interaction". The institute involves faculty from Computer Science, Mathematics, and Statistics with a focus on data science principles related to the operation of intelligent machines and their interaction with people. Applicants should be recent PhDs in computer science, math, or statistics, with an interest in working across these disciplines on applications related to intelligent machines.
TRIPODS (Transdisciplinary Research In Principles Of Data Science) is a National Science Foundation program that supports the development of collaborative Institutes that bring together the disciplines of mathematics, statistics, and computer science. The program emphasizes foundational progress in data science.
DIMACS, the Center for Discrete Mathematics and Theoretical Computer Science, is a consortium of several universities (Rutgers, Columbia, Georgia Tech, NJIT, Princeton, RPI and Stevens) and corporate research labs (AT&T, Avaya, IBM, Microsoft, NEC, Nokia, and Perspecta).
We believe that research and society benefit from a diverse workplace, and strongly encourage applications from women, minorities, individuals with disabilities, veterans, and students with non-traditional backgrounds.
Experience: This position is intended for a person who has completed a Ph.D. in Computer Science, Mathematics, Statistics, Operations Research or a related field within the last three years (or is about to graduate).
Knowledge/Skills/Abilities: Selection is based primarily on demonstrated --foundational-- excellence within the relevant areas of mathematics, statistics, theoretical computer science, data science, AI, and related fields.