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for interoperable messaging that inform future innovations and policy Applicants must have a Master’s degree in computer science, human-computer interaction, or a closely related field. Due to the project's focus
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crystallinity. Therefor prior knowledge of state-of-the-art modelling software and molecular dynamics simulations and quantum mechanical calculations to elucidate the reaction mechanism, together with AI based
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projects is required. Qualifications The ideal candidate has: A strong background in manufacturing engineering, management engineering, operations management, robotics, industrial engineering, computer
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qualifications: M.Sc. degree in electrical engineering, communications engineering, mathematical engineering, mathematics, computer science or similar; Solid mathematical and analytical skills, including signal
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well as developing solution algorithms applying mathematical and computational approaches. The group has a particular focus on automated decision making in autonomous cyber-physical systems. Autonomous systems and
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The PhD stipend is financed by different innovation projects on the development of new technologies to strengthen the European bioeconomy via valorization of various types of biomass from land and
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, and material separation. Accordingly, the candidate is required to have an Engineering degree on master’s level within manufacturing engineering, automation, or computer science. Specifically, we look
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tracked from ground stations using cameras and similar sensors, and how drones can better understand their surroundings, for example, through camera-based navigation in GNSS-denied environments. The PhD
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pesticides based on double-stranded RNA(dsRNA). The project will focus on quantifying impacts on non-target organisms and uncovering mechanisms driving species-specific sensitivities. This PhD fellowship is
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be enrolled in Aalborg University Business School’s Economics, Business, and Management PhD program. The position is part of the Carlsberg Foundation-funded Green Transition Policy Centre(GreenTraC