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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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used in synergy with immunotherapy to achieve optimal immunity against lymphomas. The project also aims to uncover the mechanisms that drive resistance to immunotherapy, using methods such as spectral
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, postdocs, researchers, and industry. Your qualifications You have graduated at Master’s level or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses in
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automated planning, reinforcement learning, logic or combinatorial optimization. Furthermore, candidates should have excellent study results, very good programming skills and high proficiency in oral 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