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on the intersection of robotics and control theory. Project description: This PhD project aims to develop learning‑based methods that combine expert demonstrations with experiential reinforcement learning to enable
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a simplified lab environment. The student will work closely with a twin PhD project at Lund University, which focuses on learning‑based generation of the type of semantic information used in this work
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series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related areas, but application to dynamic systems is
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application! We are looking for a PhD student in Statistics with placement at the Division of Statistics and Machine Learning, Department of Computer and Information Science. Your work assignments As a PhD
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. To learn more on working as a PhD student at ISY, please contact: isyphdcouncil@groups.liu.se . Starting date by agreement, but we expect you to start your employment no later than December 31, 2026
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which your employment will be renewed for a maximum of two years at a time, depending on your progress through the study plan. To learn more on working as a PhD student at ISY, please contact
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the Arctic, experimental tests of climate driven changes in carbon export from land and turnover and release of greenhouse gases (CO2 and CH4 ) from headwaters, and use of machine learning and process-based
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the study plan. To learn more on working as a PhD student at ISY, please contact: isyphdcouncil@groups.liu.se. Starting date by agreement, but we expect you to start your employment no later than December 31
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. Lead and conduct research projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data
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to machine learning is well funded and continuously publishes in high impact journals. We foster a creative working environment, where you will find freedom to implement, develop, and publish research