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/ . The post offers an exciting opportunity for conducting internationally leading research on the whole spectrum of novel machine learning algorithms and practical medical imaging applications, aiming
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are looking for a highly motivated and skilled PhD researcher to work on structural surrogates of offshore wind foundations through graph-based machine learning. Our goal is to perform full-structure
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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focus will be on biomechanics, image processing, machine learning (ML), artificial intelligence (AI), and metrology, the student will also contribute to the co-design of cadaver experiments and data
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Academies of Science Engineering and Medicine Workshops. Selected candidates will have the opportunity to train for publishing in leading biomedical journals and machine learning conferences, networking with
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candidate will have strong analytical skills and substantial experience in machine learning at scale. The Prorok Lab in the Dept. of Computer Science & Technology, has a variety of robotic platforms (aerial
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/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition, applicants should be highly motivated, able to work independently, as
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science, e.g, by leading to more effective batteries. The Research Assistant/Associate will join the Machine Learning Group at the Department of Engineering, working with Prof. José Miguel Hernández Lobato