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techniques to improve video matting, sport video analysis and real-time pose estimation of (body- and head-pose) presenter. This job is expected to contribute to the development of an end-to-end Deep-Learning
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seeking candidates with a PhD degree and expertise in an area pertinent to the project and experience in: Machine/deep learning algorithms Biomedical informatics Computer Science Expertise
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particular, photo and video editing tools, and recent advances in artificial intelligence, allow non-professionals to easily falsify multimedia documents and create deep fakes. To protect against these threats
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guidelines (see: https://ellis.eu/members ). • Fluent English/Spanish communication skills (verbal and written). • Solid understanding of Pattern Recognition, Machine Learning, and Deep Learning
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Deep Learning and LiDAR development 45 Item nº4 Interview 15 Additional Information Benefits 2.250,00 € (including the apportionments of extra payments) Selection process MERIT BASED TENDER PROCESS
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climate models through cutting-edge, Bayesian (deep) hierarchical models, with AI elements. The successful candidate will publish high quality research outcomes, and present findings at national and
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estimation of presenter’s interaction. This job is expected to contribute to the development of an end-to-end Deep Learning approach for the estimation of face and body orientation of TV presenters and related
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- Federated learning- Deep neural netwokrs- 5G/6G networks- Cyber-physical Systems- Internet of ThingsCall details: https://www.uoc.edu/portal/_resources/CA/documents/recerca/Call_Postdoc_2024_EN.pdfContact
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- Federated learning- Deep neural netwokrs- 5G/6G networks- Cyber-physical Systems- Internet of ThingsCall details: https://www.uoc.edu/portal/_resources/CA/documents/recerca/Call_Postdoc_2024_EN.pdf
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PhD degree and expertise in an area pertinent to the project and experience in: ‐ Machine/deep learning algorithms ‐ Biomedical informatics ‐ Computer Science - Expertise on the implementation and