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extreme weather to cybersecurity threats. Working within the LDTRC, you will undertake a range of research tasks, including: 1) Defining the ontology and knowledge graph architecture for a scalable digital
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audiences. QUALIFICATIONS Required: Doctoral degree (PhD) in Epidemiology, Environmental Health, Biostatistics, Child Development, Public Health, or a closely related discipline Demonstrated expertise in
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, the Postdoctoral Researcher will drive research at the intersection of health data science, multimodal AI, digital twins, computational phenotyping, and responsible AI. PhD must have been received within the last
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on methods, frameworks, and architectures that transform stakeholder information requirements into interoperable semantic models, ontologies, knowledge graphs, and digital twin services. Particular
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methods (e.g., filtering, factor graph optimization, moving horizon estimation) with learning-enhanced components, including meta-learning approaches for adaptive and generalizable estimation. The candidate
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under internal company contract and in external collaborative projects etc. Key Qualifications: PhD in computer science specialised on data sharing, digital twins, distributed databases, AI, or a related
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graphs (ARGs). Research areas include statistical/quantitative/population genetics, genealogical inference, machine learning, genetic prediction, genome-wide association studies, scalable linear mixed
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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2nd August 2026 Languages English English Norsk Nynorsk English PhD Research Fellow in Algorithms and Extremal Combinatorics Apply for this job See advertisement UiB - Knowledge that shapes society
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English English PhD Research Fellow in Formal Methods and Knowledge Representation for Engineering Information Apply for this job See advertisement About the position We invite applications for a PhD