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contact Associate Professor Marte Giskeødegård, email: marte.giskeodegard@ntnu.no If you have any questions about the recruitment process, please contact PhD Coordinator/ HR Lara Bromann, email
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of Geo-information Science and Remote Sensing. Where to apply Website https://www.academictransfer.com/en/jobs/357372/assistant-professor-in-remote-s… Requirements Specific Requirements You are/have A PhD
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an interdisciplinary team of experts in biomechanics, anatomy, medical imaging, clinical sciences, and sports coaching. This PhD is ideally suited for candidates who enjoy hands-on experimental work, working with people
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document, provided at the bottom of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process. * Please note that this is a PhD level role
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unprecedented real-time visualisation of these processes, yet systematic investigation across diverse rock types and integration with predictive models remains lacking. In this PhD study, you will be performing
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heavily on ChatGPT or a similar Generative AI application, your application letter will be very … Where to apply Website https://www.academictransfer.com/en/jobs/356298/phd-position-image-description
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improvements, and promoting the Tissue Bank within the research and wider community. Kā pūkeka me kā wheako - Your skills and experience The ideal candidate will hold a PhD or Master’s degree in a relevant
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biomedical image processing. Within the scope of machine learning and computer vision, there will be freedom to suggest your own research directions, and to become acquainted with new techniques and approaches
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) Geographical information system (GIS) Geogame and digital twin with Unity or Omniverse Global positioning system (GPS), GNSS and IMU Image processing and computer vision Asphalt binder modification, asphalt
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emerging as a promising paradigm to overcome bottlenecks in conventional computing, offering ultra-fast and low-energy information processing. Recent advances include both spiking and deep learning schemes