13 mechanical-engineering-solid-mechanics-advanced-materials-fracture-mechanics-stress-and-strain-analysis PhD positions at Linköping University
Sort by
Refine Your Search
-
2 Sep 2025 Job Information Organisation/Company Linköping University Research Field Engineering » Materials engineering Chemistry » Applied chemistry Physics » Applied physics Researcher Profile
-
tailored materials design with advanced characterization methods to enable new device functionalities. The research aims to expand the capabilities of organic electronic devices by integrating light
-
application! We are looking for a PhD student in Visualization Technology and Methodology with a focus on interactive visualization, visual learning, science communication, and educational science, formally
-
30 Aug 2025 Job Information Organisation/Company Linköping University Research Field Computer science » Digital systems Technology » Information technology Technology » Interface technology
-
an interdisciplinary research project called “c/o Glass - making flat glass circular in the built environment sector”. Flat glass is a well-used material in the construction industry but has traditionally been disposed
-
array antenna systems for imaging MIMO radar in autonomous driving applications. This work will advance the design and characterization of intelligent devices and environments for wireless communications
-
efficiency, flexibility, and sustainability. Within this research project, Linköping University is collaborating with leading industrial companies to develop digital analysis and decision-support tools
-
completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses with a substantial part gained from courses in animal behaviour/behavioural ecology and evolutionary biology
-
per cent of full-time. Your qualifications You have graduated at Master’s level in biology or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses with a
-
applications towards materials science. Generative machine learning models have emerged as a prominent approach to AI, with impressive performance in many application domains, including materials discovery