Sort by
Refine Your Search
-
Postdoctoral Associate to investigate the neural mechanisms underlying continual learning in humans. The successful candidate will develop computational models examining the tradeoff between task
-
within any of the relevant disciplines of the humanities, social sciences, and computer sciences are welcome to apply. The ideal candidate is a postdoctoral scholar seeking to examine and develop research
-
: The requirements for the applicants include: Ph.D. in Electrical Engineering, Computer Science, Operations Research, Applied Mathematics, or related fields Strong background in game theory, mechanism design, control
-
into the conditions required to launch jets. The main objective of the research program of the PI is to uncover the nature of relativistic jets and understand the connections between accretion and ejection
-
university with a fully integrated liberal arts and science undergraduate program in the Arts, Sciences, Social Sciences, Humanities, and Engineering. NYU Abu Dhabi, NYU New York, and NYU Shanghai, form
-
research university with a fully integrated liberal arts and science undergraduate program in the Arts, Sciences, Social Sciences, Humanities, and Engineering. NYU Abu Dhabi, NYU New York, and NYU Shanghai
-
completed a Ph.D. in fields such as Computer Science, Applied Mathematics, Data Science, Engineering, or related disciplines by the time they assume their post. Review of applications will commence
-
computation. In compliance with NYC?s Pay Transparency Act, the annual base salary range for this position is $62,500 - $70,000. New York University considers factors such as (but not limited to) the specific
-
experimental and computational groups within the center. Successful applicants will be highly motivated with an interest in working in theoretical and computational chemistry and have research experience in
-
risks in variable and uncertain geologies. The researcher will be embedded in a team that spans infrastructure resilience, computational geomechanics, and data-driven risk evaluation. The successful