AcademiaNet: Profiles of Leading Women Scientists

AcademiaNet: Profiles of Leading Women Scientists
AcademiaNet is a database of profiles of excellent female researchers from all disciplines. Learn more about the project.

Are you looking to appoint to committees or seeking an expert on a certain topic? Find the right scientist at AcademiaNet!


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First Scottish AcademiaNet meeting brings together leading female scientists in Scotland

AcademiaNet scientists were invited to attend the event at the Royal Society of Edinburgh to discuss gender balance in science as well as the impact of Brexit on British research.

Testimonials

  • Liselotte Hojgaard
    “The launch of AcademiaNet was a magic moment. I am proud that we also recommend our excellent female researchers.”
    Prof. Dr. Liselotte H Højgaard, Chair of the Danish National Research Foundation
  • Philip Campbell
    “AcademiaNet will become even more important as work to address gender imbalance accelerates.”
    Dr. Philip Campbell, Editor-in-Chief of Nature
  • Anne Glover
    “It’s not always easy to find good people. And I say again that’s one reason that AcademiaNet is very, very useful.”
    Prof. Anne Glover, Vice-Principal External Affairs & Dean for Europe, University of Aberdeen, Former Chief Scientific Adviser to the President of the European Commission
  • Jean-Pierre Bourguignon
    “More and more countries are realizing the importance of having women academics in leading positions in science. AcademiaNet helps to find appropriate candidates with excellent knowledge, experience and networks.”
    Prof. Jean-Pierre Bourguignon, President of the European Research Council

In Focus: Education

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Dr. Maria Anisimova

ETH Zürich

Area of specialisation

Bioinformatics, computational genomics and modeling molecular evolution

Research interests

Together with my students I work on theoretical aspects of modeling molecular evolution as well as data-driven applications of our new methodologies. We are broadly interested in applying computational methods to study the process of gene and genome evolution and in particular the process of adaptive genetic change. Growing genome-scale sequences and information from complimentary disciplines of transcriptomics, proteomics and metabolomics have begun to seriously impact genomics. But the challenge of understanding the dynamics of such large-system data can only be met through an integration of organism, molecular, and mathematical disciplines. New techniques need to be developed for discovering complex patterns from multi-faced systems biology data.


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