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The candidate should preferably have a PhD in Computer Science or Robotics with a solid background on deep learning and 3D scene understanding. Experience with LiDAR and Computer Vision is a plus. The candidate
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radiologist degree with clinical experience in clinical imaging A doctorate (PhD) in a related scientific discipline Field experience in radiographers' education, including theoretical teaching and supervision
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radiologist degree with clinical experience in clinical imaging A doctorate (PhD) in a related scientific discipline Field experience in radiographers' education, including theoretical teaching and supervision
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Application procedure: Interested candidates should send an e-mail with their CV, their transcripts and two possible referee contacts to marco.corneli@univ-cotedazur.fr and emmanuelle.vila@mom.fr
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: Programming in Python and/or R Data science (e.g., tidyverse, pandas) Machine learning (e.g., scikit-learn) Deep learning (e.g., PyTorch, Keras3) (Optional) bio-signal processing and brain imaging (e.g., EEG
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procedure. In this context, the proposed PhD project aims to develop an innovative strategy to evaluate the efficiency and quality of surgical care. This strategy is based on data science, combining
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Description This PhD project bridges computational neuroscience and machine learning to study the mechanisms of active forgetting—or unlearning—through the lens of both biological and artificial systems
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number of techniques routinely used in the lab including histology, confocal microscopy and image processing. Prior expertise in cell culture, image analysis and coding would be highly appreciated. Part of
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Keywords Optogenetics, 2-photon activation, large scale electrophysiological recordings, mouse model Lab description Processing of auditory information in the brain is complex because information
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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