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, localization, and sensing, with a focus on developing next-generation multiple-antenna systems while optimizing overall system performance. As a doctoral student, you devote most of your time to doctoral studies
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that enable energy-intensive industries to plan and optimize their production based on energy demand, power consumption, and sustainability. The current PhD position focuses on analyzing how digitalization and
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of scientific data, e.g. from image acquisition modalities or scientific simulations. Efficient algorithms are at the core of most of these data analysis and visualization applications. The focus of this Ph.D
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consist of the following: Mathematical analysis of ecological and eco-evolutionary models, involving pencil-and-paper calculations; Computer simulations of more complex models which do not easily lend
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transcripts records with grades. A copy of your Masters thesis or link to the published version. We welcome applicants with different backgrounds, experiences and perspectives - diversity enriches our work and
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the applicant: - For the dissertation and the subject relevant knowledge and skills, for example demonstrated strong background knowledge at advanced level especially related to automatic control, optimization
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successfully conducting research as well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks, data-driven modeling, learning control, optimization, and sensor
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systems, complex networks, data-driven modeling, machine learning, optimization, and sensor fusion. The division has extensive collaborations both with industry and other research groups around the
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approach that integrates wireless communication, computer vision, and machine learning to optimize PC transmission from sensors to an edge server for remote registration. The research is funded by Wallenberg