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international and dynamic team of researchers investigating problems in information retrieval (IR) and natural language processing (NLP) and their applications to health and medicine. The successful candidate
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judiciary Have experience with large language models, information retrieval, evaluation of ML systems, and deploying applications; this is highly desirable Have an excellent command of English; German
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reconstruction to overcome these challenges. Your tasks - develop physics-informed, self-supervised learning approaches for phase retrieval - implement reconstruction algorithms on HPC clusters for large-scale
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tomography and local adaptive reconstruction to overcome these challenges. Your tasks develop physics-informed, self-supervised learning approaches for phase retrieval implement reconstruction algorithms
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). For more information about our work, please visit our webpage: https://liu.se/en/organisation/liu/isy/cvl . For more information about ISY, go to: https://liu.se/en/article/open-positions-at-isy
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you think this position is relevant and interesting, we encourage you to apply, regardless of gender, functional ability and cultural background, or whether you have been out of work for a period
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curiosity, independence, and teamwork. More information about the division is available at: https://liu.se/en/organisation/liu/isy/rt . For more information about working at the Department of Electrical
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, please visit https://www.iwm.org.uk/research/doctoral-awards For informal enquiries, please contact the lead co-supervisor Dr Grace Huxford, grace.huxford@bristol.ac.uk
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on the grounds of consent given before withdrawal thereof. Providing personal information is voluntary. More information on the protection of personal data: https://port.lukasiewicz.gov.pl/en/data-protection
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biology of infection. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/ The future of life science is data-driven. Will you be part of that change? Then join us in