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- Eng-PhD-05-25 Understanding Runoff Dynamics in Small Flash-flood-prone Catchments - Eng-PhD-06-25 Improved defect detection of Guided Wave Inspection Using Machine Learning-Driven Signal Processing
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and secondments. • Blended Learning Approach: Our training combines intensive in-person workshops at partner institutions with regular interactive online seminars, journal clubs, and research
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. Current XAI methods are often generic and overlook industrial realities. This project will embed user-centric explanations directly into machine learning workflows using structured, ontology-driven
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/structural/mechanical engineering with experience and interest in structural dynamics, vibrational analysis, train-track-bridge interaction, signal processing, data science and machine learning. The successful
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. You will also spend 3 months at Georgia Tech/Emory University (USA), working on machine learning and data benchmarking. Work description The selected PhD student will be responsible for the full
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failures before they occur, enabling proactive maintenance strategies. Anomaly Detection Mechanisms: Implement machine learning techniques to identify and classify anomalies in electronic systems, enhancing
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), biostatistics, machine learning, data science and research data management, and causal inference methods (Iris Pigeot, Marvin Wright, Vanessa Didelez), and etiologic and molecular epidemiology (Konrad Stopsack
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, programming, signal analysis or machine learning are particularly valuable. If you are keen to apply technology to improve global healthcare, we would be delighted to hear from you. Entry requirements
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(predictive) modelling, for example machine learning approaches. Experience in conducting field work in polar or alpine regions. Strong and preferably demonstrated interest in interdisciplinary work at the
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, epidemiology, high dimensional statistics, infectious disease, machine learning and mathematical modelling. The centre has numerous collaborations with leading biomedical research groups internationally and in