24 computer-engineering-network PhD positions at Chalmers University of Technology in Sweden
Sort by
Refine Your Search
-
failures. We offer access to unique experimental data and computational tools developed by our research team for addressing a timely societally relevant problem. Project overview The aim is to unravel
-
The Department of Architecture and Civil Engineering (ACE) at Chalmers University of Technology has approximately 250 employees, encompassing a broad theoretical and practical knowledge base. In ACE, the Division
-
Rosén and Andreas Lindhe (Department of Architecture and Civil Engineering ). We have a strong network with national and international organizations within academia, public authorities and industry. About
-
Environment at Chalmers University of Technology, Department of Mechanics and Maritime Sciences . You will be joining an interdisciplinary team with Ida-Maja Hassellöv and external collaborators Amanda Nylund
-
This PhD position at Chalmers University of Technology offers an exciting opportunity to work in an interdisciplinary environment and receive training and support in materials design and synthesis
-
Join the cutting-edge RAM³ project: Unlocking the Potential of Recycled Aluminium through Machine Learning, High-Throughput Microanalysis, and Computational Mechanics. We are offering a PhD position
-
the Swedish National Infrastructure for Computing (SNIC) and the Chalmers Centre for Computational Science and Engineering (C3SE). Learn more about the project and the research: Project overview Due
-
modelling at both catchment and road scales, incorporating input from relevant stakeholders.The candidate will gain extensive knowledge in hydrological modelling, climate adaptation, road engineering, and
-
We are searching for a doctoral candidate eager to take part in crossdisciplinarity work within battery technology for a sustainable future. This work will compose both theoretical and experimental
-
Engineering and Autonomous Systems division . We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and learning