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science, machine 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
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, data science, medical imaging, and/or biomedical informatics Federated learning Machine/deep learning Medical image analysis Multi-source data integration Interpretability and visualisation Uncertainty
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statistics Containerized workflows and DSLs, e.g.: Nextflow, SnakeMake, Familiarity with deep learning libraries like TensorFlow and Pytorch would be a plus Collaborative tools Competences Project management
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, SnakeMake, Familiarity with deep learning libraries like TensorFlow and Pytorch would be a plus Collaborative tools Competences Project management Interdisciplinary research Capacity to work independently
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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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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