911 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions in Sweden
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will be found on our career site: https://www.oru.se/english/career/available-positions/applicants-and-external-experts/ The application deadline is1st of April, 2026. We look forward to receiving your
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research - Analytical skill - Other documented knowledge or experience that may be relevant to doctoral studies in the subject. All applicants will be informed when the recruitment is completed. https
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testing and collaboration with infrastructure owners or managers - Experience in supervision - Knowledge of data-driven methods, signal processing, or machine learning - Familiarity with sustainable
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today and in the future. For more information: http://www.slu.se/en/departments/forest-ecology-management/ Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about
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conducting research "in the wild" (e.g., field deployments or data collection in real-world environments) Familiarity with current AI technologies (e.g., machine learning, large language models) and an
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to contribute to a positive work environment. We also value the ability to work independently in carrying out work tasks, as well as openness to learning new skills and taking on new responsibilities. We value
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a strong constellation of both traditional applied biostatistics and expertise in artificial intelligence and machine learning, which is undergoing rapid development. The clinical activities
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–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience collaborating in interdisciplinary research teams A doctoral
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technology, and to build a Swedish quantum computer). Within AQP, the group of Anton Frisk Kockum has the overarching goal of providing humanity the tools to understand and use large quantum systems. Working
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complex behavior under demanding operating conditions presents a significant modeling challenge. This project addresses that challenge by combining machine learning with constitutive modeling, while