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-series analysis of PET-CT data o Develop a methodological formalism for integrating heterogeneous biomedical data o Gather knowledge in advanced statistical learning methods o interact with the researchers
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. Required Skills and Candidate Profile The project is intended for a candidate with: ➢ Skills in medical image processing and deep learning adapted to clinical applications. ➢ A good knowledge of Python
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· Assist in writing deliverables, reports, and scientific publications linked to TEF infrastructure operations and lessons learned. · Participate in workshops, knowledge exchanges, and technical
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a powerful model for uncovering muscle-specific protective processes. Yet, significant gaps in our knowledge have hampered advancement in this field including the lack of molecular markers and
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Pasteur and aims at understanding hearing from both a fundamental and clinical perspective. It combines various approaches from genetics and cell biology to biophysics and from human cognition and
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result that we aim to prove is the data efficiency of the LiDAR-VLM model. As this model is packed with semantic information and knowledge of geometric relation among points, they should require less
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Organize training sessions Library packaging and deployment The successful candidate will master the following skills and knowledge: Proficiency in modern C++ (C++14 and above) Software engineering and
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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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insights into humoral immunity. This knowledge also informs the development of novel immunogens, vaccine strategies, and therapeutic antibodies with broad and potent activity to fight human infections
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Title of the project: Genetics of brain diversity in autism The laboratory: Human Genetics and Cognitive Functions Unit (Dir. Thomas Bourgeron) Duration of the contract: 2 years The aim