The Emergent AI Center welcomes the following new projects:
- Neural network-based approaches for multiscale modelling of topological defects
Prof. Dr. Friederike Schmid, Dr. Karin Everschor-Sitte - Machine learning prediction of Odorant Receptor (OR)-ligand interactions: Chemical communication as the basis of swarm intelligence
Prof. Dr. Miguel Andrade, Prof. Dr. Susanne Foitzik - Computational performance of autistic-like networks
Prof. Dr. Martin Heine, Dr. Arthur F Bikbaev, Jun-Prof. Dr. Susanne Gerber - How emergent is the Brain?
Prof. Dr. Heiko Luhmann, Jun-Prof. Dr. Maik Stüttgen, Prof. Dr. Illia Horenko - Application of machine learning algorithms to search for dark-matter signals in spectroscopic data
Prof. Dr. Dmitry Budker, Prof. Dr. Stefan Kramer - Deep Learning of natural selection in population genomic data
Dr. Yoan Diekmann, Prof. Dr. Joachim Burger - Repetitive DNA and the ‘C-value enigma’ of genomics
Prof. Dr. Thomas Hankeln, Prof. Dr. Miguel Andrade - Learned Structures for Big Data in Bioinformatics
Prof. Dr. Bertil Schmidt, Prof. Dr. Thomas Hankeln, Prof. Dr. Andreas Hildebrandt
For more information on the individual projects, please take a look at the research part of the website