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have: Experience with AI and machine learning for medical images Experience working with data from multiple hospitals An interest in rare disease research. Additional information Informal enquiries
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language processing, historical linguistics, and computational humanities. The postholder will lead the computational stream of the project, which involves building a large corpus of Latin texts (data collection and
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are seeking a postdoctoral research associate to lead an innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a
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relevant for hadron collider synchrotrons at the high-energy frontier, such as the Large Hadron Collider (LHC) and its High Luminosity upgrade (HL-LHC) at CERN, the European Laboratory for Particle Physics
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large-scale data analysis, data mining and machine learning.�� Given the transdisciplinary nature of the team developing this programme, the role will primarily be based in CRASSH (the Centre for Research
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To undertake research on the evolution of prokaryotic pangenomes using machine learning and AI approaches. The work will involve the analysis of large prokaryotic genome datasets, the development
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, and computational humanities. The postholder will lead the curated stream of the project, which involves designing a large corpus of Latin texts, curating it (correction of pre-processed data and corpus
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experimental chemistry, providing a supportive research environment. Applicants should have a PhD in Chemistry or related field, and extensive experience in python programming and machine learning models
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, which involves building a large corpus of Latin texts (data collection and pre-processing), mining dictionary data, and developing novel algorithms for time-sensitive word sense disambiguation (WSD) in
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collaborative links thorough our collaborative network. The researcher should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely related field. You have an