Göttingen Graduate Center for Neurosciences, Biophysics, and Molecular Biosciences

Hauschild, Anne-Christin, Jun.-Prof. Dr.

Junior Professor for Medical Informatics


  • 2016 Dr. rer. nat, Saarland University, Saarbrücken, Germany
  • 2016 – 2018 Post-Doctoral Researcher Princess Margaret Cancer Centre
  • 2016 – 2018 Post-Doctoral Researcher Krembil Research Institute
  • 2018 – 2019 Visiting Research Fellow Ontario Cancer Research Institute
  • 2018 – 2019 Post-Doctoral Research Fellow Center for Addiction and Mental Health
  • 2019 – 2021 Head of Medical Informatics Division University of Marburg
  • Since 2021 Junior Professor, Institut of Medical Informatics, University of Göttingen




Major Research Interests

• Integration of machine learning in clinical decision support systems for analysis of clinical, imaging and omics datasets for disease stratification and prediction.
• Longitudinal modelling for disease progression and treatment optimization using multi- omics and medical imaging data.
• Systems medicine algorithms and network analysis approaches for biomarker detection in medicine, drug target identification and a systematic way to uncover molecular mech- anisms and pathways.
• Development of novel privacy preserving learning algorithms to improve medical re- search and foster advances health care applications.


Homepage Department/Research Group
in preparation



Selected Recent Publications

  • Park Y, Hauschild AC, Heider D (2021) Transfer Learning Compensates Limited Data, Batch-Effects, And Technical Heterogeneity In Single-Cell Sequencing. bioRxiv
  • Park Y, Heider D, Hauschild AC, (2021) Integrative Analysis of Next-Generation Sequencing for Next-Generation Cancer Research toward Artificial Intelligence. Cancers * ISSUE COVER
  • Hauschild AC, Eick L, Wienbeck J, Heider D (2021) Fostering Reproducibility, Reusability, and Technology Transfer in Health Informatics. iScience
  • Spänig S, Mohsen S, Hattab G, Hauschild AC, Heider D (2021) A large-scale comparative study on peptide encodings for biomedical classification. NAR genomics and bioinformatics. 3 (2), lqab039
  • Marshe V, Maciukiewicz M, Hauschild AC, Islam F, Qin L, Tiwari A, Sibille E, Blumberger D, Karp J, Flint A, Turecki G, Lam R, Milev R, Frey B, Rotzinger S, Foster J, Kennedy S, Kennedy J, Mulsant B, Reynolds C, Lenze E and Mueller D (2021) Genome-wide analysis suggests the importance of vascular processes and neuroinflammation in late-life antidepressant response. Nature Translational Psychiatry