AI for Oncology
PI: Prof. Dr. Christin Seifert
Institution: University of Duisburg-Essen
Department: Institute for Artificial Intelligence in Medicine (Institut für KI in der Medizin, IKIM)
Research topics: artificial intelligence in oncology.

Algorithmic Foundations and Education
PI: Prof. Dr. Johannes Fischer
Institution: TU Dortmund University
Department: Computer Science
Research topics: data structures, ML-free text indexing, text compression, combinatorics on strings, parallel algorithms, algorithm engineering.
Other affiliations: SFB 876

Algorithms for Reproducible Bioinformatics
PI: Dr. Johannes Köster
Institution: University of Duisburg-Essen
Department: Institute of Human Genetics, University Hospital Essen
Research topics: reproducible data analysis, variant calling, spatial transcriptomics.
Other affiliations: Medical Oncology, Harvard Medical School, Harvard University, Boston, USA

Bioimage Informatics
PI: Prof. Dr. Axel Mosig
Institution: Ruhr University Bochum
Department: Faculty for Biology and Biotechnology
Research topics: bioimage informatics, computational pathology, pattern recognition and explainable machine learning.
Other affiliations: ProDi

Bioinformatics and Computational Biophysics
PI: Prof. Dr. Daniel Hoffmann
Institution: University of Duisburg-Essen
Department: Faculty of Biology
Research topics: mathematical and computational models for biological systems, Bayesian analysis; applications to developmental biology, virology immunology, cancer research, or ecology.
Other affiliations: ZMB

Clinical Bioinformatics
PI: PD. Dr. Martin Eisenacher
Institution: Ruhr University of Bochum
Department: Medical Proteome Center
Research topics: computational quantitative proteomics.
Other affiliations: ProDi

Computational Biochemistry
PI: Prof. Dr. Elsa Sánchez-García
Institution: University of Duisburg-Essen
Department: Faculty of Biology
Research topics: theoretical approaches to investigate the structural properties and reactivity of complex chemical and biological systems.
Other affiliations: ZMB

Computational Biodiversity
PI: Dr. Daniela Beisser
Institution: University of Duisburg-Essen
Department: Faculty of Biology, Chair of Biodiversity
Research topics: Next-generation sequencing data analysis, (meta-)omics analysis, method development with applications in biodiversity, ecology and microbiology.
Other affiliations: SFB 1439 (RESIST)

Computational Chemical Biology
PI: Prof. Dr. Paul Czodrowski
Institution: TU Dortmund University
Department: Chemical Biology
Research topics: AI and chemical biology, effects of protonation on the binding of small molecules to proteins.
Other affiliations: nfdi4chem

Data Science
PI: Prof. Dr. Folker Meyer
Institution: University of Duisburg-Essen
Department: Institute for Artificial Intelligence in Medicine (Institut für KI in der Medizin, IKIM)
Research topics: microbiome analysis, data integration, data exchange standards, data privacy.

Genome Informatics
PI: Prof. Dr. Sven Rahmann
Institution: University of Duisburg-Essen
Department: Institute of Human Genetics, University Hospital Essen
Research topics: algorithmic bioinformatics, string algorithms and data structures, sequence analysis, hashing and applications, machine learning applications in bioinformatics; applications to human disease, cancer, microbiology and biodiversity.
Other affiliations: Computer Science XI, TU Dortmund University; SFB 876; GRK 2535 (WisPerMed)

Mathematical Statistics with Applications in Biometrics
PI: Prof. Dr. Katja Ickstadt
Institution: TU Dortmund University
Department: Faculty of Statistics
Research topics: spatial and spatio-temporal point process modelling with applications in biology and epidemiology, Gaussian process modelling and analysis with various applications, Bayesian methods and Markov Chain Monte Carlo techniques, regression methods for very large, high-dimensional data, classification and clustering methods for genetic data.
Other affiliations: SFB 823; SFB 876; GRK 2624

Medical Machine Learning
PI: Prof. Dr. Dr. Jens Kleesiek
Institution: University of Duisburg-Essen
Department: Institute for Artificial Intelligence in Medicine (Institut für KI in der Medizin, IKIM)
Research topics: image analysis, self- and unsupervised learning, federated learning, multimodal data analysis.

Statistical Methods in Genetics and Chemometrics
PI: Prof. Dr. Jörg Rahnenführer
Institution: TU Dortmund University
Department: Faculty of Statistics
Research topics: applications of statistics in genetics, bioinformatics and medicine, both regarding method development and data analysis; statistical analysis of gene expression data, statistical analysis of clinical data, survival analysis, cluster analysis
Other affiliations: SFB 823; SFB 876; GRK 2624