Project overview

Methods from machine learning for big data are to be applied to questions in atmospheric physics. Among other things, the representation of clouds in climate models and the predictability of weather situations will be worked on.

The Carl Zeiss Foundation awards scholarships to outstanding young scientists from the STEM fields to attend the Lindau Nobel Laureate Meetings.

Prof. Dr. Anne Stumper of Aalen University is researching a novel diagnostic approach for the independent monitoring of bodily fluids following initial treatment for conditions such as leukemia.

Prof. Mürsel Yildiz, Professor of IT Security in Digitalization at Nordhausen University of Applied Sciences, is researching AI-supported cyber security. He is developing an LLM-supported model that detects and responds to security threats at an early stage.

Prof. Dr. Laura Maria Comella, Professor of Intelligent Embedded Systems at Karlsruhe University of Applied Sciences, is developing a precise optical measurement system for the leaf area index (LAI). The aim is to better understand and organize forest ecosystems.

Dr. Victor Ksoll conducts research in the field of astrophysics. He studied physics at the University of Heidelberg, where he completed his doctorate in astronomy with research stays at the Institute of Planetology and Astrophysics in Grenoble, France and at the Space Telescope Science Institute in Baltimore, USA.

Dr. Alexander Behnke researches the biological mechanisms of mental illness. He studied psychology at the TU Dresden, obtained his doctorate at the University of Ulm and most recently worked as a postdoctoral researcher at the University of Ulm and Columbia University.

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.

Wafer-level packaging is a chip manufacturing technology. It increases integration densities and reduces the use of materials and energy. The project aims to bring new material concepts and 3D printing technologies to production maturity.

The aim of the project "Medical AGI's Last Exam" (MEDAL) is to develop a particularly demanding and at the same time practice-relevant test for the evaluation of medical imaging AGIs and to provide the associated data. This test is intended to serve as a comprehensive reference test for general AI systems in the field of medical imaging.