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discipline. Prior experience in any of the following is a plus but not essential: ultrasound or wave physics, numerical simulation, Python programming, and machine learning frameworks. Most importantly, we
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Python programming. ● Experience in monitoring code performance. ● 3 or more years of demonstrable experience in machine learning theory. ● Excellent communication and teamwork skills. ● Proficiency in
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modeling, geometric deep learning or physics-informed machine learning, or you are willing to learn these quickly; strong collaboration skills: you enjoy working in a multidisciplinary team and feel
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-Physical Energy Systems The PhD position focuses on the development of secure and trustworthy AI for resource-constrained embedded systems. The research will investigate how machine learning models can be
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and cooperation. You have a strong interest in machine learning/artificial intelligence. You have a strong interest in graph-based learning (e.g., graph neural networks). You have experience with deep
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researchers from diverse backgrounds. Good communication skills and a willingness to learn are important for working effectively within and beyond the consortium. Candidates should hold a Master’s degree in
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advanced analytical approaches, including deep learning and machine learning, to improve disease subtyping and risk prediction. You should have a strong willingness to learn, enjoy tackling challenging
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attention to quality, integrity, creativity and cooperation. You have a strong interest in machine learning/artificial intelligence. You have a strong interest in graph-based learning (e.g., graph neural
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 2 months ago
. The successful candidate will be expected to carry out the following scientific activities: Application of advanced Machine Learning, Deep Learning, reduced-order modelling, and physics-informed/-guided modelling
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
analysis, image analysis, statistical, and machine learning methods, choosing the approach that best fits the scientific question. Investigate systematically what information is contained in imaging data