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will engage with large-scale longitudinal health data, develop and validate computational models, and contribute to methods that will enable pathogen-resolved population research across the lifespan
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10 Apr 2026 Job Information Organisation/Company Lunds universitet Department Lunds universitet Research Field Geosciences Researcher Profile First Stage Researcher (R1) Application Deadline 22 Apr
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, longitudinal patient and population registries and biobanks. Project description Large language models (LLMs) enable the extraction of clinical information from unstructured medical text. However, current LLM
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ontologies, and domain-specific language models, among many other methods and models. You will engage with large-scale longitudinal health data, develop and validate computational models, and contribute
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values rest on credibility, trust and security. By having the courage to think freely and innovate, our actions together, large and small, contribute to a better world. We look forward to receiving your
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is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture. The ongoing societal transformation and large green investments in
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information on annual incomes and household composition, making it possible to reconstruct both income and expenditure. To add a dynamic dimension, the project follows female-headed households over time and
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is required in both written and oral communication. Documented quantitative skills are required. Experience in statistical programming, data management, and working with register data or large micro
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merits experience in statistical programming and statistical analysis experience in data management, and working with register data or large micro-level longitudinal databases experience in working with
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of possible methodological components include self-supervised temporal representation learning for large volumes of unlabeled AE/electrochemical time-series data, switching state-space models that describe