326 web-programmer-developer "https:" "https:" "https:" "https:" "https:" "https:" "University of Kent" research jobs in Sweden
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Stage Researcher (R1) Country Sweden Application Deadline 16 Jan 2026 - 22:59 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not
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Deadline 12 Feb 2026 - 22:59 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Horizon Europe - ERC Is the Job related to
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representatives: https://internt.slu.se/en/my-employment/employee-associations/kontaktpersoner-vid-rekrytering/ The Swedish University of Agricultural Sciences (SLU) has a key role in the development
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available in the research group of Prof. Dr. Jan Streuff. The planned project deals with the development of new titanium(III)-catalyzed reactions, more information can be given during the interview
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for everyone to develop in the subject and as a person. Subject description Structural Engineering includes loads, design, sustainability, load carrying capacity, repair and strengthening, of buildings and civil
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. Is proficient in modern statistical modelling, AI & machine learning methods (e.g. system identification, regression models, Bayesian methods, deep learning). Is an experienced programmer in R and/or
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combines metabolomics, microbiome science and computational modelling to develop new food intake biomarkers and to understand individual metabolic responses to diet and develop personalized nutrition
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and food web dynamics in northern lakes, informing both conservation and sustainable management of aquatic ecosystems. The position is part of a broader research program on biodiversity and ecosystem
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lifecycle management. At the same time, the project delves into software design concerns, focusing on the internal structure and evolution of AI-enabled components themselves, including the design of
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application! Work assignments This position focuses on the development of theoretically grounded and practically scalable decentralized learning algorithms under realistic system constraints, including