Sort by
Refine Your Search
-
Country
-
Employer
- Harvard University
- University of Oslo
- Carnegie Mellon University
- Cyprus University of Technology
- IDAEA-CSIC
- NTNU Norwegian University of Science and Technology
- Naturalis
- The Cyprus Institute
- University of California
- University of Idaho
- University of Michigan - Ann Arbor
- University of Rhode Island
- 2 more »
- « less
-
Field
-
. ________________________________________________________________________________________________________ About URI: The University of Rhode Island enrolls approximately 17,000 students across its graduate and undergraduate programs and is the State’s flagship public research university, as well...
-
approaches such as variational autoencoders and diffusion models. The resulting workflow will train AI models on paired virtual diffraction data and known ground truth, then validate and refine them using
-
of the department. No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. Job description The PhD fellow will contribute to the development of an observing system for land
-
Carnegie Mellon University is a private, global research university that stands among the world’s most renowned education institutions. With ground-breaking brain science, path-breaking performances
-
of an observing system for land-atmosphere fluxes of carbon, water, and energy in arctic environments. Observations from eddy flux towers, drones carrying meteorological sensors and gas analyzers, soil sensors, and
-
Profile Recognised Researcher (R2) Positions Postdoc Positions Application Deadline 1 Sep 2026 - 23:59 (Europe/Oslo) Country Norway Type of Contract Temporary Job Status Full-time Is the job funded through
-
the interaction between body, computation, and environment, in various types of flying, ground-based, and aquatic robots. Our mission is to chart a generalisable path for physical AI and transform how robot
-
ground- and drone-based measurements—along with satellite data, into land-surface and boundary-layer models, drawing on the department’s unique infrastructure of eddy flux towers, drone platforms, and data