Silja Heilmann

Silja Heilmann

Postdoc

I am a postdoctoral research scientist, with a background in physics, who currently studies epithelial morphogenesis in the developing pancreas. I am particularly interested in how cells communicate, differentiate and orientate themselves influenced by mechanical forces. At the moment I am enthusiaticly using/learning about machine learning techniques such as deep learning, to improve 3D image processing and analysis.     
 
During my biophysics Ph.D. studies in the Biocomplexity group at the Niels Bohr Institute (NBI), I did theoretical work on microbial ecosystems. I realised then, that a theoretical trained person like myself, needs strong collaborations with experimental biologists in order to do truly impactful research in biology. A deep understanding of experimental methods and a knowledge of biological lingo is crucial for a theorist to influence the research of an experimental collaborator and transcend the role of a mere data analyst. Therefore, during my two postdoc positions at Memorial Sloan Kettering Cancer Center and Novo Nordisk Foundation Center for Stem Cell Biology, I have immersed myself in experimental biological environments in order to nurture strong close collaborations with experimental biologists. 

I am generally interested in the fields of Cancer, Stem cell and Developmental Biology since I think they offer the most exiting research questions as well as the possibility to impact lives. How do blobs of spherically symmetric stem cells self-organise into complex structures of polarised differentiated cells in mature organs? How do organ structure and symmetry break down as cancer progresses and tumor cells regress to a stem cell like state? These are the types of questions I wish to continue to address via mathematical/statistical tools and finite element modeling based on data extracted from 3D fluorescence microscopy images generated by my colleagues in the Semb group at DanStem (Novo Nordisk Foundation Center for Stem Cell Biology). 


 
 
 
 

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