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application! Work assignments Subject area: Computational studies of the influence of microstructural features on the structural integrity of metallic materials using machine learning Subject area description
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mathematics, ecology, history, climatic and medical sciences in collaboration across multiple institutes. An integral part of the project is to develop process-based eco-epidemiological models considering
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of myocarditis through a systems medicine approach. By integrating data from genomics, virology, immunology, metabolomics, and microRNA analyses, all derived from well-characterized patient cohorts, we aim
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GENESIS – Generative AI Agents for Software Engineering: Skills, Integration, and Satisfaction. The project is a multi-year collaboration with Ericsson and Axis Communications, aiming to investigate and
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Ecology, Resistance Biology and Integrated Plant Protection research, providing excellent opportunities for strong research collaboration within and outside the departmental area. Research efforts
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to integrate functional measurements from live human pancreatic tissue with multiomic measurements to identify key factors driving diabetes. To achieve this, we are employing a broad array of
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-, and fuel-related Risk Influence Factors (RIFs). Translate potential risk scenarios into Unity-based extended reality (XR) modules and embed proactive Risk Control Options (RCOs). Integrate developed
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includes the PI, a PhD student, and a research expert in bioinformatics. The workplace fosters strong international collaboration, with close integration with the Halberg Group at Copenhagen University
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expected to integrate existing and new datasets into publishable manuscripts. Your profile The successful candidate must have: - A PhD in a discipline such as Environmental Sciences, Ecology, Forestry
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at the division of Statistics and Machine Learning (STIMA) or Artificial Intelligence and Integrated Computer Systems (AIICS). Read more about STIMA: https://liu.se/en/organisation/liu/ida/stima Read more about