Budapest.Physics_of_Cancer

A postdoctoral position is available to join the recently established Evolutionary Genomics Research Group funded in 2016 under a highly competitive 5 year grant from the Hungarian Academy of Sciences' "Momentum" program as well as an ERC Starting Grant starting in 2017.

Research Topic:

Cancer is a genetic disease fuelled by somatic evolution. Despite advances in the molecular biology of cancer associated genes and the recent surge in the amount of DNA sequences available for different cancers, our understanding of the evolutionary mechanisms that lead to cancer is limited and cancer mortality rates have changed little in the last few decades. Until we unravel cancer's basic principles, the battle against it can only progress in inches, rather than in miles.

To address the problems quantitatively, a new field called the "physics of cancer" has emerged. In the context of this emerging field the Evolutionary Genomics Research Group works to understand the evolutionary process that leads to the breakdown of the hierarchical organisation of healthy tissues and the emergence of tumours, using evolutionary models, computer simulations, and sequence analysis. We do this with the aim of developing models that can predict how cancers respond to treatment depending on their functional and genetic diversity and guide us toward developing  novel treatment strategies and improving existing ones. In our most recent work (Derenyi & Szollosi 2017) we asked how tissues generate large numbers of cells while at the seam time minimising the accumulation of mutations and the risk of cancer.

To answer the question we introduced a general model of hierarchically organised self-renewing tissue and derived the lower limit of lifetime divisional load of a tissue. We showed that hierarchically differentiating tissues can approach this limit, and that this depends on uneven divisional rates across the hierarchy. We are looking for a postdoctoral researcher to build on these results and work with us in exploring the evolutionary process that lead to breakdown of hierarchical organisation of healthy tissues. The questions that we want to answer include: Under what conditions do hierarchically differentiated tumours, i.e. “cancer stem cells”, evolve? Which kind of mutation lead to cancer and in what combination, e.g. do mutations that increase symmetric vs. asymmetric cell division rate drive tumour progression or vice versa?

Derenyi, I & Szollosi, GJ Hierarchical tissue organization as a general mechanism to limit the accumulation of somatic mutations Nature Communications in press (2017)
https://doi.org/10.1101/098129

Position Details:

The successful candidate will either have a PhD in Evolutionary or Computational Biology or come from a strong quantitative background such as Physics,  Applied Mathematics or Statistics with the ambition to pursue research in Evolutionary Biology.

The position is for up to 2 years with the possibility of extension and a salary of up to 2,000 EUR per month conditional on experience (adjusting for cost of living this corresponds to approx. EUR 3,000 in Berlin, 3,300 in Vienna and 4,200 in Paris [numbeo.com] ).

The research group is lead by Dr. Gergely Szollosi ( https://scholar.google.hu/citations?user=sPrYT-oAAAAJ ) and Prof. Imre Derenyi ( https://scholar.google.hu/citations?user=kDEAL-wAAAAJ ).

The research group is hosted at Eotvos University's Institute of Physics. The Institute of Physics has been included in the Excellence Group of European Universities, and has achieved top placement in the number of citations, the number of ERC grants, the time available for PhD research and the gender balance of masters students in the CHE Excellence Ranking. The research group is associated to the Depts. of Biological Physics and Complex Systems composed of several interdisciplinary research groups including those of Prof. Imre Derenyi, Prof. Tamas Vicsek, and Prof. Istvan Csabai. 

Please direct all enquiries to Dr. Gergely Szollosi (ssolo@elte.hu). Applications are accpted until the poistion is filled. Please include a CV with list of publications (preferably referencing a google scholar profile) and a motivation letter addressing the research topic described above.