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You have academic qualifications at PhD level, for example within the areas of bioinformatics, machine learning or forensic odontology. We favour experience in computational data analysis, and the
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of solid oxide cell and stack materials Commissioning, modifying, and maintaining testing equipment Developing new mechanical testing methods Preparing samples for mechanical testing, and carrying out post
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provide assistance in organising workshops and advisory board meetings. The post is for two years and represents an exciting opportunity to acquire valuable research experience, to contribute
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Monitoring (LTVEM) in the hospital for management and diagnosis of epilepsy. The technology is built on brain computer interfaces equipped with a Spiking Neural Network (SNN) and aims at early detection
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observations, and remote sensing data to assess the impact of global change on ecosystem productivity and sustainability. You will develop novel algorithms to integrate data-driven machine learning and process
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Communication, Singal Processing, Low Power Electronics, Wireless Sensing, Low-Power System Design, Machine Learning & Edge Inference, Underwater acoustic communication. Furthermore, you have a proven record of
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approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed at uncover the key traits that define successful microbial biofertilizers
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Job Description DTU Sustain’s section Waste, Climate and Monitoring offers a 2-year position as a post-doctoral fellow in detection and quantification of fugitive emissions of poly- and
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submitted your application, you must send this person’s details (name, job title, place of work, and email address) as well as the name of the position you have applied for to: HR.Nattech@au.dk Formalities
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equal gender distribution. We are located in Lyngby, Hirtshals, Nykøbing Mors, and Silkeborg and have regular activities in Greenland. Learn more on aqua.dtu.dk Technology for people DTU develops