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, computer vision, robotics, biomedical engineering, computer science, biomechanics, neuroscience, signal processing, or a closely related discipline. Strong expertise in machine learning and deep learning
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archaeological signatures (e.g., micro-relief, edge structures, etc.) – Design and implementation of new deep learning architectures (both supervised and unsupervised/few-shot, 2D and 3D) for an efficient and
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Università degli Studi di Roma Tor Vergata - Dipartimento di Biomedicina e Prevenzione | Italy | about 2 months ago
phenotypes. The post-doc will implement machine-learining and deep-learning fusion piplelines to combine high-dimensional imaging features and-omics data, building interpretable ipredictive models. Activities
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be invited for an online interview with the selection committee. Join us in Vilnius – one of the top-rated cities for work-life balance globally! Learn more about the quality of life and opportunities
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. – knowledge of computer vision; knowledge of deep learning architectures; – Knowledge of C++, Python, Matlab; – Analog/digital circuits IC design capability; – Testing of electronic devices and systems; FPGA
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experimentation of novel deep learning models, both unimodal and multimodal, with the aim of understanding and predicting processes and dynamics in complex fields such as artificial vision and signal processing
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learning and deep learning techniques to the biological sciences. The ideal candidate will have expertise in artificial intelligence, with a specific focus on deep learning applications in structural biology
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, Python or similar) Specific Requirements Interest in optical imaging and interferometry. Prior knowledge will be a plus Interest in computational methods, image processing and machine/deep learning. Prior
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analog, requiring the model to integrate multimodal inputs to anticipate the onset and spatial evolution of ionospheric storms. The successful candidate will work at the intersection of deep learning and
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). Desirable assets are: • Machine learning, deep-learning, artificial intelligence, advanced statistical inference; • A solid record of research activities, including relevant publications in international peer