Here you will find an overview of the projects we are currently funding. On average, about 150 projects are being funded. Smaller funding projects are sometimes not described individually.
206
ongoing projects
MAINCE will use AI approaches to identify new and much-needed therapeutics in immunology. Clues to the effect of therapeutics through state-of-the-art imaging techniques will be linked by AI to laboratory experiments to accelerate drug development and make it more efficient.
Prof. Dr. Rainer Gasper has been appointed as Endowed Professor of Mechatronic Systems Engineering at Offenburg University of Applied Sciences starting summer semester 2019.
Dr. Sina Saravi is a physicist specializing in nano-optics. He studied electrical engineering in Iran and then completed his doctorate in physics at the University of Jena, where he has been working as a postdoctoral researcher since 2018.
The establishment of a centre for model-based artificial intelligence is intended to improve the treatment of cancer. It is investigating how AI systems can support cancer research more efficiently through pre-programmed knowledge.
The project team is researching the treatment of heart failure using a combination of novel AI approaches and robotics. Comprehensive health data will be used to train an AI that will identify new correlations between the disease and the values and incorporate them into the therapy.
The "Smart Neighbourhood Jena-Lobeda" is used to examine how a multigenerational neighbourhood with working and living space can promote self-determined living into old age through intelligent digital technologies.
Prof. Dr. Dirk Koch has been appointed to the professorship for Novel Computing Technologies at Heidelberg University starting April 2022. He previously conducted research at the University of Manchester, UK.
Pollen-related respiratory allergies affect up to 30% of the world's population. Climate change is further exacerbating the problem. However, forecasting pollen fields is extremely difficult. PollenNet aims to provide a more accurate and up-to-date forecast of local pollen loads.
How can artificial intelligence simplify manufacturing processes and contribute to quality assurance? For quality assessment in the process, among other things, an expert system is being set up and digital twins are being used.
The project is about bringing together machine learning and physical modelling. The two funded junior professors are looking at process engineering processes from basic material data to industrial processes.