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include modeling of bulk and single-cell transcriptomic profiles, integrative multi-omics analysis, and the fusion of molecular data with clinical and imaging features. Organizational Status The successful
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UiO/Anders Lien 9th February 2026 Languages English English English Join a vibrant team at the University of Oslo as a PhD Research Fellow in Deep Learning for geoscience imaging! PhD Research
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to mitigate equine musculoskeletal health risks. · Collect and process data within the disciplines of epidemiology, diagnostic imaging and pathology, using state-of-the-art technologies. · Write
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related fields. Additional optional skills and qualifications: Experience in deep learning for medical imaging. Contracting requirements: Presentation of the academic qualifications and/or diplomas
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the dielectric properties and physical properties of interest. Learning Objectives: The participant will be trained on assembling, testing and calibrating microwave sensors for measurement of the dielectric
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experimental skills related to high-speed imaging, X-ray imaging, data acquistion, and signal filtering are also appreciated Interest in the translation of fundamental physics to real-world applications Modes
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pathomechanisms and developing prototype drug candidates. Project outcomes will be protected as intellectual property and will provide a foundation for translation through clinical studies and appropriate
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. laser scanning, thermal imaging) for process monitoring and optimisation; • Excellent communication and collaboration skills. • Open to fixed-term contract. Desired: • Hands-on experience with
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 25 days ago
estimation in robotics, stochastic control in systems and control theory, stochastic image processing or probabilistic computer vision). The School/Department The School of Engineering brings together a
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of maintenance. The project aims to develop an integrated decision-support framework that combines inspection images, sensor data, and engineering interpretation to enable more transparent, evidence-based