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This PhD project will investigate the structural basis of bacterial pili-mediated adhesion, a critical process in host colonization and biofilm formation. Using an integrative structural biology
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research and soft robotics development. PhD project The PhD project will focus on the technical aspects of simulating the physics of the Drosophila larva body. The primary objectives include: Developing a
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exciting opportunities for machine learning to address outstanding biological questions. The PhD student to be recruited will be working on the development of machine learning methods for single-cell data
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environmental physics affects larval actions Develop robust APIs for community access Required Qualifications Essential: Strong background in finite element methods and numerical simulation Proficiency in Python
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on large-scale genetic and environmental data to identify relevant exposures and gene-environment interactions. Method Development: Develop novel statistical and computational methodologies to address
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, and deep learning, our goal is to identify new antibiotics and their modes of action. To make these methods accessible to the scientific community, we are developing an open-source platform that will
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of 4 months. Phd possibility : This internship may lead to a PhD position for motivated candidates. Contact : dbc-epi-recrutement@pasteur.fr References : [1]: C. Eschbach et al, Nature Neuroscience
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interactome techniques. Expected profile: The applicant should have a PhD in cellular biology or neurobiology. Experience in molecular biology, primary culture maintenance and/or CRISPR technology and/or
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» BiologyEducation LevelPhD or equivalent Skills/Qualifications Required qualifications: Recent PhD degree (including in late 2025) in tumor biology, vascular biology, immunology or related biomedical field, with
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international meetings. – Draft manuscripts and contribute to future grant proposals. We are seeking a highly motivated early-career scientist with: – A PhD in Life Sciences (immunology or cell biology). – Solid