Sustainable Plastics from Plants

TU Graz is coordinating the European B3PO Doctoral Network, which is developing innovative materials from plant by-products. The EU has supplied funding of EUR 4.3 million for the project.
TU Graz is coordinating the European B3PO Doctoral Network, which is developing innovative materials from plant by-products. The EU has supplied funding of EUR 4.3 million for the project.
At the Go International! Fair on 16th October, Exchange Coordinators and students with experience abroad give advice on mobility programmes: for students of TU Graz – including joint study programmes…
One topic, but a multiplicity of angles and perspectives.
Energy storage systems are becoming increasingly important, powerful and widespread. However, this also means that the demands on their safety and durability are growing.
By combining physics-based methods with machine learning, a team at the Institute of Thermodynamics and Sustainable Propulsion Systems at TU Graz is developing models that deliver better results…
IoT devices without a dedicated power supply: this is the research focus of an international consortium that includes TU Graz. The EU has provided EUR 8.4 million in funding for the project, which is…
A team of students from TU Graz, TU Vienna, the University of Vienna, JKU Linz and St. Pölten UAS has qualified for the final round of the unofficial hacking world championship in Las Vegas.
Alexander Lex is looking at the question of how interaction between humans and computers can be improved – particularly in visualisation and accessibility.
The Artificial Intelligence Engineering extension programme offers master’s students and graduates the opportunity to learn the basics of computer science and apply AI methods to their specialist…
Do you dream about developing a race car, creating biological systems, building rockets or robots, or steering a car with the power of thought? Seize your chance and join one of our student teams.
Researchers from TU Graz, Pro2Future and the University of St. Gallen have developed methods that enable IoT devices to run AI models with minimal memory – for example, to correct positioning errors.
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