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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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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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.-equivalent degree (or evidence of its completion in the nearest future) preferably in Computer Science, AI, Bioinformatics or relevant field. The candidate should have: Experience with deep learning and AI
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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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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
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muscle recordings. The position will focus on developing new methods for analyzing neuronal dynamics based on deep learning techniques to extract different neuronal subspaces related to states of the
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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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learning and deep learning to various different data modalities. An ambition of this team is to implement predictive modelling as well as explainable AI methods to understand disease drivers leading to early
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Principal tasks and duties: Study of proposals and research work on Machine Learning and Deep Learning (ML/DL) techniques that are applicable to multiple tactical domains in cyber defence environments, with
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: climate data processing (observations, reanalysis and climate models), development, application and validation of statistical methods based on deep learning algorithms for the statistical downscaling