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catalysts for the synthesis of a range of industrially valuable compounds. This PhD project is part of the Horizon Europe Marie Sklodowska-Curie Action (MSCA) doctoral network (DN) ELEGANCE (machinE LEarning
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, statistics, or mathematics OR a strong background in gene engineering and functional interrogation of hematopoietic stem and progenitor cells. Strong knowledge in bioinformatics, machine learning, statistics
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of greenhouse gases including CO2 and CH4. The PhD project is part of the Horizon Europe Marie Sklodowska-Curie Action (MSCA) doctoral network (DN) ELEGANCE (machinE LEarning for inteGrated multi-parAmetric
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computing and machine learning—unlocking new possibilities for precision metrology and non-destructive evaluation (NDE) in modern industry and healthcare. This PhD will push the boundaries of next-generation
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Prof. M. Fernando Gonzalez-Zalba, a multidisciplinary and dynamic research team passionate about building a scalable quantum computer based on silicon technology. Moreover, the PhD will have a strong
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. Background: You hold a PhD in Computer Science, Machine Learning, Electrical Engineering, Embedded Systems or related fields. Core Expertise: Strong expertise in Federated Learning and/or Continual Learning
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approaches for using machine learning to analyze X-ray data, particularly Resonant Inelastic X-ray Scattering (RIXS). The position will collaborate with experts in RIXS experiments (Mark Dean), computational