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preserving AI; machine learning; large health register data; GDPR compliance rules; and clinical research. Qualification requirements PhD stipends are allocated to individuals who hold a master’s degree. PhD
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for representation learning, uncertainty quantification, and model interpretability over large, heterogeneous datasets such as sequenced microbial DNA fragments coupled with auxiliary environmental data. Starting date
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energy storage materials, particularly in Li-ion batteries will be considered as a big advantage. Excellent skills in oral and written English are required. The applicant must be interested in working in
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recognized lab working on different aspects of AI. Focus has previously been on visual data but has recently been expanded to cover also other data modalities including textual data. See more about the
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language processing approaches to analyse large-scale textual data from scientific publications, patents, industry documents, and policy sources. The work includes creating reproducible workflows for processing
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, the focus of the PhD project is to develop a methodology to digitalize the recycling line of spent LIBs from EVs for a large-scale application, while integrating existing research. Specifically, the project