2200 København N.
My research as a computational biologist focuses on developing data-driven algorithms and data integration to harness the power of large-scale genomic data - in other words: biological data science applied to biological 'big data'.
My research centers around developing computational algorithms to better understand the molecular underpinnings of human diseases and complex traits - at a single cell level. I focus on integrating single-cell tramscriptomics and large-scale human genetic data to learn disease biology and interpret heterogeneity in single-cell populations – particularly in context of the brain and metabolic diseases. My long-term research goals involve applying these tools to large-scale genomic and heterogeneous biomedical data to improve disease treatment and healthcare.
Primary fields of research
Biomedicine, human genomics, single-cell biology, bioinformatics, machine learning
I am always looking for talented students motivated to do research projects within bioinformatics, data science or statistics.
Description of available student projects: Decoding biology using machine learning and single-cell transcriptomics
Please email me if you are interested in hearing more about the opportunities for doing an internship or student research project.