Sort by
Refine Your Search
-
learning based materials modelling Communicate your research by presenting your results in scientific journals and at international conferences The position generally also includes teaching on Chalmers
-
wastewater systems. Research environment The project is based at the Division of Water Environment Technology (WET), within the Department of Architecture and Civil Engineering. You will be part of
-
Project overview Climate change and increasing flood risks pose significant challenges to urban infrastructure worldwide.While many municipalities are exploring catchment-based approaches
-
developing AI methods for automated microstructure analysis and 3D microstructure generation. By combining self-supervised learning and diffusion-based generative models, the goal is to: Reconstruct high
-
to investigate flow-induced forces in hydraulic turbines under varying operational conditions and how these forces affect the degradation and lifetime of the machines. About the position The position is based
-
. Based in a beautiful Nordic city with close access to nature, you will enjoy a competitive salary, full social benefits, and work-life balance. As part of our research group, you will benefit from: A
-
) The doctoral student will be based at the Division of Building Design and within the research area Architectural Design, Dwelling and Values. The division focuses on sustainability, circularity, sufficiency and
-
introduces new and underexplored vulnerabilities to network-based threats. The goal of this research is to uncover such threats, evaluate their impact on training performance and model integrity, and develop
-
the development of fiber spinning processes and the integration of the resulting fibers into wearable devices, such as fiber-based organic electrochemical transistors. In addition, tensile testing, dynamic
-
, they introduce new and understudied attack surfaces. The research aims to uncover novel network-based threats targeting these systems and to develop robust countermeasures. By systematically identifying