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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
computer vision and/or audio(-visual) machine learning (e.g., multi-object tracking, speaker/source localisation, multimodal fusion). Experience with deep learning frameworks (PyTorch or equivalent) and
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research, preferably with 3D modelling skills. ¿ Foundational expertise in machine learning and big data analytics Job Summary Postdoctoral Researchers support teams of KSU faculty and students
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
-tier machine learning and computer vision venues, actively participating in departmental seminars, and contributing to collaborative projects. Where to apply Website https://jobs.inria.fr/public/classic
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, and computer vision. In particular, it focuses on the measurement of eye-gaze as a key window into cognition, integrating experimental, comparative, and computational approaches. We aim to move beyond
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We are seeking a postdoctoral researcher with a curiosity-driven record who works at the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy
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). The researcher should have a PhD/DPhil in robotics, computer vision, machine learning or a closely related field. You have an excellent academic track record in topics relevant to robot perception. A specific
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Learning (ML), Deep Learning (DL) particularly in Natural Language Processing (NLP) and Computer Vision (CV) - strong record of publications - Excellent communication skills and ability to work in a fast
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learning (ML). Our lab explores the intersection of artificial intelligence, and human-computer interaction, striving to create technologies that amplify human potential. The successful candidate will engage
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the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy to consider candidates in one of the two fields who can demonstrate a strong basis for working in this cross
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well as machine learning and multivariate decoding of neuroimaging data to predict subjective experiences and individual differences. Successful candidates will be supported in building a research program at the