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) Limited until: 30.09.2029 Reference no.: 6194 Explore and teach at the University of Vienna, where more than 7,500 academics thrive on curiosity in continuous exploration and help us better understand our
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Auditory SCEnes in Humans and Machines), an ERC Synergy project conducted in collaboration with Dr. Bruno Giordano (CNRS, Marseille). NASCE brings together cognitive neuroscience, advanced neuroimaging
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, with attention to scientific quality, reproducibility, and continuous learning. Communicate, present, and collaborate effectively, including explaining technical ideas clearly and presenting research
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machine learning and physics to recover nanoscale information from imperfect images? Modern computer chips are built with features only a few nanometers across, yet manufacturers need to measure these
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learn new things - A strong programmer who’s comfortable with Python - An open-minded thinker and precise communicator who enjoys collaborating with colleagues from a wide range of backgrounds and areas
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The project will be carried out primarily at the CLLE laboratory (UMR 5263) at University of Toulouse – Jean Jaurès (UT2J), in collaboration with the Institut de Recherche en Informatique de Toulouse (IRIT
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machine learning. The project combines methodological research in statistics with applications to large-scale social science data. The successful candidates will have the opportunity to collaborate closely
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foundations of medical deep learning. The project focuses on novel self-supervised objectives, information geometry, mitigating representation bias for rare pathological findings, and building next-generation
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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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Join the Responsible Machine Learning (ML) Group at the Faculty of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research