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Wikibase instance Curate and model historical migration datasets within the dedicated Wikibase instance Contribute to the design of ontologies and metadata schemas for the knowledge graph Develop data-driven
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) dual-site research and training facilitated by a virtual research environment (VRE) where digital classes are combined with online tools to share information and research data a comprehensive
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) dual-site research and training facilitated by a virtual research environment (VRE) where digital classes are combined with online tools to share information and research data a comprehensive
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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data Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will
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technique. If successful, this could pave the way to nano-optical read and write heads for future data storage as well as to direct sequencing of nucleic acid and protein sequences by scanning-probe Raman
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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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); dual-site research and training facilitated by a virtual research environment (VRE) where digital classes are combined with online tools to share information and research data; a comprehensive
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biological data, development of deep learning and large language models for biological discovery or graph-based methods for molecular and cellular networks. The technological foundation further consists
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protocols and generation of data, we can offer a challenging job in a dynamic research environment. The successful applicant will be placed in the research unit Ruminant Nutrition: https://anivet.au.dk/en