Derzeitige Tätigkeit: Wissenschaftliche Mitarbeiterin bei Boehringer Ingelheim

Forschungsgebiet: developing and applying machine learning algorithms to solve biomedical questions; enzyme function prediction based on cheminformatics descriptors and translated the methodology to predict the solvation free energy of crystalline drug-like molecules; developing machine learning methods for medical applications, using deep learning for peak annotation and ECG disease classification; processing and analyzing molecular OMICs data, e.g. in identifying radiation induced alteration in human gingiva fibroblasts from exome sequencing data, or in analyzing transcriptome data to characterize the impact of MALAT1 deficiency in atherosclerosis development; novel biomarkers for thyroid dysfunction - developing machine learning algorithms to mine genetic and clinical data and identifying novel risk factors and their interrelation in disease progression

Programmteilnahme: Postdoktorandinnen 2019

Externe Mentorin: Dr. Edda Schulz, Max-Planck-Institut für molekulare Genetik, Max Planck Institut Berlin

Interne Mentorin:Prof. Dr. Elke Krüger, Institut für Medizinische Biochemie und Molekularbiologie, Universitätsmedizin Greifswald