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    Opportunity: PhD position in a Marie Skłodowska Curie European ITN: Bioinformatics pipelines development for virome classification @ University of Bordeaux -- Bordeaux, France
    Submitted by Marie Lefebvre; posted on Wednesday, May 01, 2019


    We are looking for a PhD student with the background in computer and information sciences who would like to join the Bordeaux Bioinformatics Center with the aim to participate in a Marie Skłodowska Curie European Innovative Training Network project "INEXTVIR".

    This is a full-time position for 3 years, during which you will be employed at University of Bordeaux, France. You will be working on research project "Bioinformatics pipelines development for virome classification". During the project you will undertake mobility (travel to other partner organisations in INEXTVIR project) in order to implement your individual Research Project, as well as to participate in complementary training activities.

    • Dr Macha Nikolski (macha.nikolski[at], Senior CNRS scientist and team leader for Bioinformatics with a extensive experience in sequence analysis and in particular in the use of HTS-approaches for virus characterization and metagenomics.
    • Dr Katarzyna Hooks (katarzyna.hooks[at],


    The project aims to develop bioinformaric computational methods for the analysis of HTS data in the context of plant virome studies. More precisely, the ESR will
    1) Define and apply bioinformatic pipelines to detect viruses from HTS datasets in a computationally efficient manner.
    2) Define rules and implement a method for the inter-sample contamination detection.
    3) Design and develop new methods for homology free machine-learning specifically tailored for virome classification and for virome / microbiome interaction analysis.
    4) Integrate the resulting pipeline within a user-friendly graphical system (such as Galaxy) providing a complete bioinformatics analysis workflow from raw sequencing reads.


    • Masters or equivalent, preferably in bioinformatics, computer science or data science
    • Good mastery of English, strong communication skills and teamwork ability, dynamism, thoroughness and curiosity, basic French is a plus.


    Main location: Bordeaux, France

    Secondary location:
    • ULIEGE (academic) 2 months to learn how machine learning approaches can be used for plant virome data
    • Biosistemika (non-academic) 2 months for the aspect of delivery of bioinformatics pipelines (docker development, interface etc)
    • UPM (academic): 4 weeks to learn about how environmental diversity considerations should impact the design of an alignment-free virome analysis pipeline


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