{"id":3693,"date":"2022-02-12T11:27:54","date_gmt":"2022-02-12T10:27:54","guid":{"rendered":"https:\/\/gradschool.eiphi.ubfc.fr\/?p=3693"},"modified":"2022-02-13T14:04:00","modified_gmt":"2022-02-13T13:04:00","slug":"eiphi-research-project-coquiiaj","status":"publish","type":"post","link":"https:\/\/gradschool.eiphi.ubfc.fr\/?p=3693","title":{"rendered":"EIPHI Research Project : COQUIIAJ"},"content":{"rendered":"\n
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Recently, the global industry is facing a fourth revolution, called Industry 4.0. It refers to the connectivity and integration of intelligent and autonomous systems to collect and analyse data and digitise the organisation’s operations. Indeed, by adding smart cameras to production lines, we are seeing improved defect detection quality at high speeds and reduced costs. Furthermore, given the restrictions imposed on human labour by the COVID-19 law, such as social distancing in the factory, these benefits are even more essential to keep production lines running. In order to address this issue, our objective in this project is to create a digital twin of the production line based on image analysis and Artificial Intelligence (AI). The aim is to combine the AI expertise of the DISC department with the non-conventional imaging know-how of the IMVIA laboratory. This twin will enable the generation of realistic synthetic images. These images model the various acquisition systems set up on the production line. They will then be used to train an AI for defect detection.<\/p>\n\n\n\n

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This project is held by FEMTO-ST and ImViA and is supported by the Bourgogne Franche-Comt\u00e9 region and the National Research Agency (ANR): <\/p>\n\n\n\n

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One Ph.D and One Post-Doctorate positions are opened for this project. To apply please contact directly by email the person in the job files below :<\/p>\n\n\n\n

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Ph.D Position :<\/strong><\/p>\n\n\n\n

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ImViA Multimodal image synthesis for AI-based quality control<\/a><\/p>\n\n\n\n

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Post-Doctorate Position will open in september 2022:<\/strong><\/p>\n\n\n\n

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FEMTO-ST Deep learning for multimodal imaging<\/p>\n\n\n\n

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