AI_PYTHON_EN Telegram 2378
با تشکر از دکتر آرش ربانی برای ارسال این موقعیت تحصیلی هر کدوم از دانشجوها علاقمند به اپلای هستند اقدام کنند.
A fully funded Ph.D. position in computer science at the University of Leeds! We are looking for an outstanding international or UK-based applicant to join our research group (Data Flow Lab) at the school of computing. The project title is “3D reconstruction of porous material based on 2D images using conditional generative adversarial neural networks (CGANs)”. If you are interested in Generative Adversarial Neural Networks, functional material, porous media, and 3D image analysis, don’t miss the opportunity! We will be working closely with the school of geoscience and medicine to study realistic images of geological and biological porous material. For more information and to express interest, please be in touch through email ([email protected]).

FindAPhD page link: https://www.findaphd.com/phds/project/3d-reconstruction-of-porous-material-based-on-2d-images-using-conditional-generative-adversarial-neural-networks-cgans/?p154984
University page link: https://phd.leeds.ac.uk/project/1597-3d-reconstruction-of-porous-material-based-on-2d-images-using-conditional-generative-adversarial-neural-networks-cgans
Research group link: www.DataFlowLab.org



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با تشکر از دکتر آرش ربانی برای ارسال این موقعیت تحصیلی هر کدوم از دانشجوها علاقمند به اپلای هستند اقدام کنند.
A fully funded Ph.D. position in computer science at the University of Leeds! We are looking for an outstanding international or UK-based applicant to join our research group (Data Flow Lab) at the school of computing. The project title is “3D reconstruction of porous material based on 2D images using conditional generative adversarial neural networks (CGANs)”. If you are interested in Generative Adversarial Neural Networks, functional material, porous media, and 3D image analysis, don’t miss the opportunity! We will be working closely with the school of geoscience and medicine to study realistic images of geological and biological porous material. For more information and to express interest, please be in touch through email ([email protected]).

FindAPhD page link: https://www.findaphd.com/phds/project/3d-reconstruction-of-porous-material-based-on-2d-images-using-conditional-generative-adversarial-neural-networks-cgans/?p154984
University page link: https://phd.leeds.ac.uk/project/1597-3d-reconstruction-of-porous-material-based-on-2d-images-using-conditional-generative-adversarial-neural-networks-cgans
Research group link: www.DataFlowLab.org

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