12 master-"https:" "https:" "https:" "https:" "UCL" positions at Institut Pasteur in France
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The HUB : https://research.pasteur.fr/en/team/bioinformatics-and-biostatistics-hub/ Degree: Master degree in computer science, computational biology, bioinformatics or similar Relevant skills : Hard skills
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following skills: Strong interest in the field of neuroimaging, psychiatry and genetics. Computer skills: Strong level in the main informatics software (FSL, Freesurfer, fMRIprep) and coding languages (R
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) – presentation of results at conferences – interaction with team members and international collaborators Required skills : Degree : Master of Physics, data science, computer science, applied mathematics We expect
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required. The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative- genomics/) at Institut Pasteur, led by Laura Cantini, works at
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% with Laura Cantini’s team and 20% with the Bioinformatics and Biostatistics HUB. Information about the teams : The Machine Learning for Integrative Genomics team : https://research.pasteur.fr/en/team
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Master would be ~€45K gross/year at ~€2,970 net/month Salaries can be adjusted to the specificities of the candidate Application Process Please submit: CV with publication list (if applicable) Contact
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will have expertise in molecular and cellular biology and will notably perform labelling and imaging by STED of primary culture, modification of the cells by CRISPR-Cas9 to introduce mutations, and
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on structural data. More information and applicaiton : https://positions.stradivarious.eu/jobs/6722909-dc11-ehec-type-iv-pili-structure-host-adhesion-and-signalling
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Network spanning 33 institutes worldwide. Host laboratory: The Mass Spectrometry for Biology Lab https://research.pasteur.fr/en/team/mass-spectrometry-for-biology/ )led by Julia Chamot-Rooke, is a dynamic
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Host Lab our lab (https://research.pasteur.fr/en/team/cellular-plasticity-in-age-related-pathologies/ ) explores how cellular senescenceorchestrates tissue repair and regeneration. We focus on how