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of deep neural networks in the field of adaptive processing of graph data (Deep Graph Learning) . The developed novel approaches will be applied to case studies in bioinformatics Requirements Additional
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develops solutions for a range of vision tasks via machine learning and deep learning algorithms. The SSUDIO project aims to identify various objects of interest from shipboard 3D scans by training computer
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Experience in programming, expertise in software for handling big data, with a special emphasis on deep learning methods, and especially language models. 30% Complementary Training Having knowledge of software
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Description Completion of doctoral thesis related to: Process and analyze experimental data. Develop predictive models using deep learning. Train, validate, and optimize neural networks (CNNs, etc.) applied
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CORE A*/A conference paper. We invite applications for a postdoctoral position focused on the development of predictive models for clinical outcomes following Deep Brain Stimulation (DBS) in Parkinson’s
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) Application and further development of deep learning methods for automated object recognition and classification in point clouds and 3D data Establishment of a data processing pipeline for the efficient
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criteria Experience in writing documentation on the topic of Deep Learning Website for additional job details https://www.utcluj.ro/media/jobs/2025/DOC154_GAlboYR.pdf Work Location(s) Number of offers
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microfluidics, nano-electronics, nano-biomaterials, big data, and deep learning. Applicants must hold an M.D., Ph.D., or equivalent degree and have extensive postdoctoral experience, along with a strong
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development in topics such as computer vision, audio signal processing, machine learning, deep learning, and/or sensor systems. Experience in collaboration and technology transfer to partners outside
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multilingual or speech impairment contexts. Programming Skills Strong proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow. Experience with web development (e.g., FastAPI, Flask