Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- National Aeronautics and Space Administration (NASA)
- Oak Ridge National Laboratory
- Cornell University
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Aalborg University
- Delft University of Technology (TU Delft)
- SUNY Polytechnic Institute
- Technical University of Munich
- Texas A&M University
- Umeå University
- University of Twente
- Aix-Marseille Université
- Autonomous University of Madrid (Universidad Autónoma de Madrid)
- Brookhaven National Laboratory
- CNRS
- George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș
- Istituto Italiano di Tecnologia
- LNEC, I.P.
- Luxembourg Institute of Science and Technology
- McGill University
- Sveriges Lantbruksuniversitet
- Swedish University of Agricultural Sciences
- Umeå universitet
- Umeå universitet stipendiemodul
- University of Liverpool
- University of Liverpool;
- University of Nevada, Reno
- University of Oxford
- University of Southern Denmark
- University of Twente (UT)
- 20 more »
- « less
-
Field
-
Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Do you want to develop human-centred RL algorithms to shape
-
Requisition Id 15490 Overview: The Multimodal Sensor Analytics group in the Electrification and Energy Infrastructure Division (EEID) is seeking a postdoctoral researcher with proven expertise in
-
and automated fault detection and diagnosis (AFDD) algorithms to buildings Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork
-
findings regularly. Prototype algorithms, validate outputs, and document methods clearly Collaborate asynchronously with an international team, present findings regularly Experience with remote sensing
-
principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several national and international research groups, edits one of the major
-
theory, and is expected to have experience with the practical implementation of control algorithms. Who we are Learning and Decision at AAU, founded in 2020, focuses on developing mathematical methods
-
close-to-field conditions, and (ii) a fully autonomous phenotyping robot, Phenomobile.v2+, equipped with a set of sensors (LiDAR, RGB, IR, and Spectrometer) that enable advanced plant measurements