154 parallel-and-distributed-computing-phd Postdoctoral positions at Princeton University
Sort by
Refine Your Search
-
5,200 undergraduate students and 2,600 graduate students. The University's generous financial aid program ensures that talented students from all economic backgrounds can afford a Princeton education
-
approximately 5,200 undergraduate students and 2,600 graduate students. The University's generous financial aid program ensures that talented students from all economic backgrounds can afford a Princeton
-
commitment to undergraduate teaching.Today, more than 1,100 faculty members instruct approximately 5,200 undergraduate students and 2,600 graduate students. The University's generous financial aid program
-
positions are pro-rated accordingly. The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information.
-
leading and mentoring graduate and undergraduate students. A PhD in relevant fields of energy storage, electrochemistry, and materials characterization is required. Experience with solid electrolytes
-
the School of Architecture and Associated Faculty of the Department of Computer Science. The desired start date is Spring 2025. Appointments are for one year with the possibility of renewal pending
-
research and to their own work. Eligible candidate must have less than five years of post-PhD research experience prior to anticipated start date. This is a one-year term position ideally starting September
-
. Additional Information: Applicants must also hold a PhD in demography, sociology, epidemiology, or a related field. They must also be able to regularly work in person at OPR. They will receive full employee
-
Faculty of the Department of Computer Science. The desired start date is Spring 2025. Appointments are for one year with the possibility of renewal pending satisfactory performance and continued funding
-
computational modeling techniques to study planning in rodents engaged in dynamic spatial foraging tasks. The successful candidate will develop computational models of reinforcement learning in the brain and