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total of approximately 1,400 employees and 17,700 students spread across two inspiring campus environments in Karlstad and Arvika. More information at: kau.se/en/work-with-us Description We are seeking a
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at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model reduction, with
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Arctic headwaters. It will include field studies and the use of existing data, potentially complemented with modelling. The postdoc is also expected to collaborate with project partners and carry out
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interdisciplinary research environment More information about Jönköping University as a workplace, conditions and benefits on www.ju.se . Required Qualifications Applicants must have been awarded a PhD in Computer
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information about us, please visit: www.dbb.su.se . Project description The candidate will develop machine learning (ML) strategies, primarily revolving around interpretable ML and generative AI, to study
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for further development. The postdoctoral position includes a combination of experimental work, data analysis, as well as interpretation and presentation of research results. The main part of the work for the
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, collaborating closely with the project team throughout all stages of data collection and analysis. The position will be supervised by Lennart Olsson, Professor at the Lund University Centre for Sustainability
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, imaginaries, and emerging technology-impacted practices. Detailed description of the work duties, such as: Empirical data collection, for example, policy document analysis, stakeholder interviews, participant
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evaluated and validated using uniquely integrated historical datasets comprising environmental, social, demographic, mobility, and epidemiological information. The successful candidate will contribute to a
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, the establishment and optimization of behavioral assays under controlled oxygen conditions, image‑based analyses, and quantitative data processing and interpretation. The role also includes active participation in