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application! We are looking for a PhD student in automatic control at the Department of Electrical Engineering (ISY). Your work assignments The research area for the position is complex networks and multi-agent
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participate in research education. As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or other departmental
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Institute of Technology, Chalmers University of Technology, and Linköping University. The center is based on the vision that the forest can provide sustainable bio-based alternatives to today’s fossil-based
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application! The Wallenberg Wood Science Center (WWSC) is a major research initiative between three leading Swedish universities: KTH Royal Institute of Technology, Chalmers University of Technology, and
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application! We are looking for a PhD student in automatic control at the Department of Electrical Engineering (ISY). Your work assignments You will work on a project on data driven control. In recent years
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University, and within ELLIIT. As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or other departmental
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climate scientists (read more under “Your workplace” below). As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include
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. The PhD programme includes course work amounting to 75 ECTS as well as PhD thesis work. Your qualifications The holder of the position must meet the requirements for both general and specific eligibility
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), offers an exciting opportunity to work at the forefront of AI security, tackling some of the most pressing challenges in the field. As a PhD student, you devote most of your time to doctoral studies and
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application! We are looking for a PhD student in biomedical engineering with a focus on deep learning for medical images Your work assignments The position focuses on developing methods for federated learning