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, multi-billion investments will be made in large projects in Northern Sweden to create a fossil-free society both nationally and globally. Luleå University of Technology is involved in several
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and calibration of reports from various sources. Collect and analyse large-scale cross-industry accident data using FRAM (Functional Resonance Analysis Method) within LLMs to identify human-, technical
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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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research is based on large and high-dimensional datasets across multiple modalities, including molecular, clinical and histopathology imaging data. Our computational pathology research is based
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processes. A demonstrated interest in data visualization and large-scale data analysis is highly desirable. The ideal candidate will have a keen interest in understanding complex biological systems
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predators such as seals and cormorants. One possible measure to support cod recovery, particularly the survival of large reproductively important individuals, is the use of artificial reefs. These structures
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systems, or network analysis. Experience with methods for causal inference, or modelling of biological systems is also considered a merit, along with prior work involving large-scale sequencing data such as
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, multi-billion investments will be made in large projects in Northern Sweden to create a fossil-free society both nationally and globally. Luleå University of Technology is involved in several
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within the Data Science & AI division (DSAI). With 30+ nationalities and strong industry/academic ties, we offer a dynamic, collaborative ecosystem. The AI and Machine Learning in the Natural Sciences
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of the Krycklan Catchment Study (www.slu.se/Krycklan ) are available for the project, which may also draw on data from other experimental catchments and large-sample databases. About the position This work will be