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Field
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and apply machine learning and deep learning models to analyse complex, multi-dimensional datasets, including spatial transcriptomic, proteomic, and single-cell sequencing data. The candidate will
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interpreted using deep learning to estimate tool-to-retina distance and generate accurate three-dimensional navigation commands without relying on conventional 3D reconstruction. Research Objectives
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experts in making better-informed decisions. You’ll gain expertise in 3D deep-learning, semantic technologies, explainable and uncertainty-aware AI, and human-centred evaluation, and test your work in
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have learned during the day. Using a gentle sound played during deep sleep, linked to a therapy session, we aim to help the brain hold on to the progress made in therapy. The student will use wearable
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and support well-founded decision-making within the programme. You design and organise engaging workshops and learning experiences for students, connecting digital and technological developments to real
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Are you passionate about combining the directed evolution of diverse biomolecules with deep learning approaches and contributing to the development of better (bio)catalysts and drugs? We
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AITHYRA GmbH - Research Institute for Biomedical Artificial Intelligence of the Austrian Academy of Sciences | Vienna, Virginia | United States | about 5 hours ago
(e.g. geometric deep learning, generative models, representation learning) to decode molecular physiology, pathology, and therapeutic design? Are you passionate about high-throughput biology and scalable
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. We are working
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on AI-assisted reverse engineering of integrated circuits for hardware assurance and intelligence analysis. The project is conducted within the Deep Learning for Perception and Data Science, Safety and
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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