Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. Read more: https://wasp-sweden.org/ . The vision of WASP is excellent research and competence in artificial
-
diverse community of individuals from a wide range of nationalities. As a PhD student with us, you benefit from comprehensive career development support, opportunities for networking, and access to robust
-
behavioural phenotypes and social systems develop and evolve. Specifically, the project will focus on behavioural syndromes and social networks in dogs and to some extent wolves. The selected PhD student will
-
planning -Semantic-based Exploration -Source localization -Perception in sensor-degraded environments: -Localization in smoke and dust filled environments -Scene awareness -Biometric/triage evaluations, etc
-
will be expanded with the recruitment of 19 academic and 7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of the Research School
-
postdocs at Chalmers, and collaborate with academic and industrial partners in Sweden and internationally. The role also offers opportunities for travel and engagement with external collaborators. Research
-
at the terahertz and millimetre wave division are on technologies with applications that span from basic science to future sensors and communication systems. We are at the forefront of innovation in terahertz
-
7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of the Research School. The DDLS program has four strategic research areas
-
, which is crucial for rutting, using machine learning. Second, we will develop new systems to integrate data from radar and lidar sensors mounted on drones and forestry machines to improve future real-time
-
effort at the intersection of machine learning and applied mechanics. The focus of this position is on extracting information about what a neural network has learnt in a symbolic and (human) interpretable