Sort by
Refine Your Search
-
Listed
-
Employer
- Chalmers University of Technology
- SciLifeLab
- KTH Royal Institute of Technology
- Lunds universitet
- University of Lund
- Jönköping University
- Karlstads universitet
- Kungliga Tekniska högskolan
- Linköping University
- Umeå University
- Chalmers tekniska högskola
- KTH
- Karlstad University
- Stockholms universitet
- University of Skövde
- chalmers tekniska högskola
- 6 more »
- « less
-
Field
-
, both over the wireless interface and within the core network, will be driven by AI and machine-learning applications. This research will develop efficient communication strategies to support
-
We invite applications for a Doctoral student position in applied mathematics and machine learning for urban 3D reconstruction, within the Digital Twin Cities Centre (DTCC). The project aims
-
will use advanced evaluation techniques, data mining, and generative machine learning models to create an active learning cycle to identify materials with adequate properties. Promising materials will be
-
, tightly collaborating research groups conducting research and education in Robotics and AI, Intelligent Autonomous Systems, Robot Learning, Machine Learning, Human-Robot Interaction and Natural
-
generative machine learning models to create an active learning cycle to identify materials with adequate properties. Promising materials will be synthesized, characterized and evaluated in lab. This will help
-
, or quantum-inspired methods Experience with hybrid quantum–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience
-
both nationally and internationally. Today, the Division of Solid Mechanics consists of approximately 25 employees, of which around 15 are PhD students. The work environment is open and welcoming
-
trained in leading European research environments with generous support and training by many industry partners. Within COMBINE we seek excellent open-minded and team-spirited PhD candidates who will get
-
-order modeling, or machine learning Experience collaborating in interdisciplinary research teams What you will do Develop hybrid quantum–classical methods to improve simulation and prediction
-
doctoral researchers will be trained in leading European research environments with generous support and training by many industry partners. Within COMBINE we seek excellent open-minded and team-spirited PhD