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University of Veterinary Medicine Hannover • | Hannover, Niedersachsen | Germany | about 24 hours ago
-supervisors) per PhD student University of Veterinary Medicine Hannover University location Activate map To activate the map, click on the "Show map" button. We would like to point out that data will be
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headquarters in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here
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wide range of social science methods. Key commercial sectors include (but are not limited to) data centres and high-tech industries, as well as food and beverage production. This project is a
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cell biology, protein chemistry and mass spectrometry, molecular microbiology and biophysics. For further information about the position please contact Professor Brage Storstein Andresen, PhD, FRCPath, e
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usability and accuracy, as well as conducting field tests to validate their effectiveness. Additionally, the research will explore the economic viability of these sensors to enhance real-time data collection
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due to a lack of resource. With some water-hungry sectors (such as data centres and other high-tech industries) prioritised for significant growth in water stressed regions, these challenges are set to
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studies the tropical infectious disease melioidosis. The results of her research lend credence to the premise that the disease is more prevalent in southern Africa than the official data suggest. Birnie is
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investing in your personal and professional development. For more information, please visit Working at Utrecht University . About us A better future for everyone. This ambition motivates our scientists in
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skills, project management, teamwork, and leadership helps PhD students to improve their communication and presentation abilities as well as critically evaluate their research data. Didactic Skills
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sizes and frequencies by: Measuring rock fractures from UAV data using manual and automated mapping approaches (e.g., machine learning, convolutional neural networks). Monitoring physical weathering