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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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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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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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, the applicant should not be in possession of a PhD degree at the moment of being recruited. Recruited Doctoral Researcher can be of any nationality and must comply with the following mobility condition: they must
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a 8-month postdoctoral position for investigating the risks and commercialization possibilities of a novel storage concept that consists in injecting CO2 in deep volcanic areas. The position is
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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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of Machine Learning and Data Science. Education: Computer Science Engineering or Degree. Telecommunications Engineering or Degree. MSc or PhD in the field of Computer Science. Job specific skills: Strong
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in Computer, Data Sciences or a bachelor in Biosciences. PhD in bioinformatics, data sciences, machine learning or related areas. Experience: Previous experience on the use of machine learning and data
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specifically, we are developing Deep Learning tools to detect galaxy edges or truncations (i.e. a physically-motivated size indicator based on a sudden decrement of the number of stars in the galaxy outer parts