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the ability of neural networks to learn unknown posterior distributions distributions. Their use in the field of image microscopy, however, remains limited. The purpose of this PhD thesis is to develop
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the clinic and in silico. We focus on neurodegenerative processes and are especially interested in Alzheimer's and Parkinson's disease and their contributing factors. The LCSB recruits talented scientists from
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a challenging problem. Candidate profile PhD on optimization and/or image processing. Strong background in applied mathematics, image processing, learning methods and algorithms. Good coding skills
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micro-environment (dendritic cells and anti-tumoral T lymphocytes) and to decipher how immunotherapies impact on these processes. The main objectives of this project are: – to implement single cell RNAseq
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study and other ongoing translational initiatives to develop a voice-based digital health solution to alleviate the diabetes burden. Project objective The PhD candidate will work at the interface
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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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degree with clinical experience in clinical imaging A doctorate (MD or PhD) in a relevant scientific discipline Field experience in radiographers' education, including theoretical teaching and supervision
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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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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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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