Post-Doc : Computational population genetics (Copenhagen)

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Current bioinformatics algorithms and software are often ill-equipped to deal with DNA extracted from ancient populations. This ancient DNA shows high levels of fragmentation and accumulated chemical damage. Furthermore, the number of individuals that can be sequences is often limited. Fortunately, several problems pertaining to ancient DNA and ancient paleogenetics can be described in a maximum-likelihood framework and computer science techniques can help us to solve such numerical problems efficiently via machine learning, numerical algorithms and data structures. You will work in collaboration with other partners including the University of Copenhagen in order to develop the next generation of algorithms and software applied to DNA from fossils which can then be used to reconstruct population history and infer selection.

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