-
The successful candidate will develop generative machine-learning methods for amorphous molecular thin films — the supramolecular structures that govern the performance of organic-electronic materials
-
). Quantitative analytical methods will include UPLC-MS/MS as well as mass spectrometry-based analysis of dipeptide-protein interactions, supported by rigorous statistical evaluation. The candidate will be working
-
/or QGIS) Very good English language skills, both written and spoken Basic knowledge of the German language or the willingness to acquire it for the purpose of knowledge transfer Openness, creativity
-
excellent knowledge of written and spoken English We offer Goal-oriented, individual training and development opportunities (e.g. Learn and perform sc and sn-RNA seq and data-analysis) Working with the latest