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be important. You are expected to actively contribute to joint research projects, experimental design, and data interpretation across disciplinary boundaries. Responsibilities and qualifications Your
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-mounted ground-penetrating radar (GPR) with smart meter data to transform leak detection. Drones equipped with GPR will identify underground anomalies, while smart meter data will refine localisation
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, geometallurgy or related field Experience in either stochastics, deep learning or minerals processing is needed Structured and solution-oriented working style, analytical thinking and above-average committment
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; safe handling of inert gas techniques; knowledge of analytical methods for molecular chemistry; Microsoft Office and chemical software handling; confident presentation of scientific results in English
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the mobility, ubiquity, security, and interactivity of computers, data, software, and users. The pervasive computing paradigm enables technologies such as sensors, actuators, and computers to take a back seat
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the mobility, ubiquity, security, and interactivity of computers, data, software, and users. The pervasive computing paradigm enables technologies such as sensors, actuators, and computers to take a back seat
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Applicants should hold a relevant MSc degree in electronics, electrical engineering, computer engineering, or related fields. Required Qualification: Solid background in digital CMOS design and deep learning
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to think and work independently, excellent analytical skills and strong verbal and written communication skills are also essential requirements. How to apply You must apply through the University’s Apply
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simulation and modelling tools In addition, we look for a candidate with strong communication and collaboration abilities as well as excellent problem-solving and analytical skills that have been demonstrated
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Job Description The Department of Civil and Mechanical Engineering of the Technical University of Denmark (DTU) has an open PhD position on the topic of “Automation of tool wear measurement and data