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pre-processing), mining dictionary data, and developing novel algorithms for time-sensitive word sense disambiguation (WSD) in Latin, contributing to the creation of a 100-million-token annotated corpus
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2025 Reference: 0815-25 We wish to recruit a full-time postdoctoral research associate for 3 years. You will join Lancaster Medical School (LMS) to work with Dr Jemma Kerns and collaborators to develop
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Christopher Yau (http://cwcyau.github.io ) at the Big Data Institute, University of Oxford. This post will contribute to the development of a new simulation-based pre-training framework for building more robust
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information sciences. In parallel with basic research, we develop ideas and technologies further into innovations and services. We are experts in systems science; we develop integrated solutions from care
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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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navigation algorithms and machine learning models on physical robot platforms. We are particularly interested in candidates with expertise in generative AI and curriculum learning applied to robotics, as
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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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Bioinformatics and Computational Biology headed by Ivo Hofacker. Our team works on the development of algorithms and methods for problems in Computational Chemistry, Systems Chemistry, and Computational Biology
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the Department of Computer Science and Engineering, at the University of Cambridge, UK. The Postdoc will work across several projects, interfacing with teams of students and research collaborators on developing
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to advanced control design and system optimization. Our specialty is developing embedded control, estimation, and identification algorithms that directly interface with physical hardware. We work closely with