11 digital-signal-processing PhD positions at Lulea University of Technology in Sweden
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universities worldwide. We are looking for a PhD student in Process Metallurgy who will conduct research studies in the field of iron oxide reduction and carburization using alternative hydrogen carriers. We
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, Mechatronics, Mechanical, Geophysics, or a similar education. You also have to be able to fluently speak and write in English. Topics within the degree that will be seen as meritorious are: - Signal processing
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computer systems uses data to improve their own performance, understanding, and to make accurate predictions and has a close connection to applications. Project description As a doctoral student, you will be
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interoperability and always-on artificial intelligence. To achieve the vision, research will focus on improving the hardware for both 6G devices and space-based satellites, developing signal processing methods
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solutions. This includes software-defined SoS for the automation and digitalization in production industries. Our research is conducted in close collaboration with industries such as Bosch, Ericsson, Volvo
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transformation of SMEs through cutting-edge digital innovation and circular business models. Your work will help empower companies to decarbonize, minimize waste, and build resilient, future-proof value chains
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solutions. This includes software-defined SoS for the automation and digitalization in production industries. Our research is conducted in close collaboration with industries such as Bosch, Ericsson, Volvo
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solutions. This includes software-defined SoS for the automation and digitalization in production industries. Our research is conducted in close collaboration with industries such as Bosch, Ericsson, Volvo
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visibility across distributed systems. -Security measures for hybrid cloud-to-edge architectures to protect against diverse threats. The projects aim to further digitalize the European industry, where EISLAB
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the fields of cloud computing, computer networking and immersive systems to develop elastic and cost-efficient cloud-based AI pipeline to tackle climate change and support sustainability. Some of the tasks