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                Employer- UiT The Arctic University of Norway
- University of Stavanger
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- National Research Council Canada
- Simula Research Laboratory
- University of Oslo
- Basque Center for Macromolecular Design and Engineering, POLYMAT Fundazioa
- Fritz Haber Institute of the Max Planck Society, Berlin
- Institute of Cosmos Sciences of University of Barcelona
- Institute of Systems and Robotics-Faculty of Sciences and Technology of the University of Coimbra
- Instituto Politécnico de Beja
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                rates expected by simulations have provided conflicting results. Large samples of detections are necessary, and a wealth of publicly available data exists in ALMA’s archive waiting to be examined 
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                using a large collection of digitalized patient journals. Agentic workflows to integrate, retrieve and reason over longitudinal patient information. Explainability techniques to uncover drivers 
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                journals with ongoing data collection and possibility of further expansion. The candidate will work at the intersection of AI, information retrieval, multimodal learning, and clinical decision-making 
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                25 Oct 2025 Job Information Organisation/Company Basque Center for Macromolecular Design and Engineering, POLYMAT Fundazioa Research Field Chemistry Researcher Profile First Stage Researcher (R1 
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                mechanics, data-driven approaches, and machine-learned interatomic potentials are highly beneficial but not required. We offer The 3-year Liebig PhD Fellowship is tax-free and is funded 1850 euros/month. The 
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                complex datasets. The role includes designing independent experiments, applying AI and big-data analytics, mentoring short-term students, and contributing to publications that will support the development 
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                encoded into adaptive immune receptors. The advent of high-throughput sequencing has enabled an unprecedented accumulation of big immune repertoire sequencing data. However, as of yet, we lack 
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                analysis of multi-source datasets (e.g., mechanical, process, and imaging data). Proficiency in data science techniques, large dataset handling, and Python-based programming; Experience in the publication 
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                expected to contribute to ongoing and future projects with measurements, including analyses and mathematical modelling of already collected and new data. The overarching goal is to create models that can 
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                algebra, differential geometry, analysis and computational mathematics, as well as their applications to data science and computational dynamics. You can read more about the center on its homepage