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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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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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bacteria The PhD student will work on the impact of the microenvironment of the human gut on colonisation and virulence of enteric bacterial pathogens (EHEC). In this project you will use a highly
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computational reconstruction methods based on AI (deep learning) and/or compressed sensing. The envisioned imaging system will be based on a hybrid open-top light sheet microscope recently implemented in our lab
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spoken and written is required The candidat must have a PhD in computer science, machine learning, or computational biology The position is available immediately and will remain open until filled
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significant computational component. We strongly recommend a background in machine learning and coding. Applicants with a background in areas such as computational neuroscience, reinforcement learning, or deep
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Send your CV along with a motivation letter to chloe.lehoucq@pasteur.fr with benjamin.devauchelle@pasteur.fr in Cc. The candidate should have a PhD in Neuroscience or Cognitive science and the
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learning inference on HPC or cloud clusters. Contribute to developing an open-source platform that supports FAIR data management and reproducible research. Your Profile Strong experience in Python, software
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Research Engineer/Postdoctoral Position Decision and Bayesian Computation (DBC) – Epiméthée (EPI) Laboratory Institut Pasteur, Paris | 25 rue du Docteur Roux, 75015 Paris Position Overview We
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/machine-learning-for-integrative-genomics/ The HUB : https://research.pasteur.fr/en/team/bioinformatics-and-biostatistics-hub/ Degree : PhD in computer science, computational biology, bioinformatics