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Field
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-of-the-art machine learning methods, acoustic sensing can provide valuable insight into a wide range of processes occurring within the built environment. Potential applications include structural health
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conditions, changes appear years before clinical diagnosis. Can we learn to extract them reliably? We are looking for a PhD candidate to join the Acoustics group at the Department of Electronic Systems, NTNU
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solutions that combine low energy consumption with reliable and safe operation in compliance with relevant standards and regulatory requirements. A key scientific challenge addressed in this project is the
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programme No Joint degree / double degree programme No Description/content The Konrad Zuse School of Excellence in reliable AI (relAI) offers fully funded positions for doctoral researchers in the field
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languages, including Python, C++, or Java, focusing on algorithms and data structures applied explicitly in computer vision projects Knowledge of machine learning and deep learning frameworks, including
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demanding and methodologically challenging. In realistic applications, uncertainty arises from multiple sources, including parametric uncertainty, model-form and structural assumptions, numerical
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, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the
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required. Structured, reliable, and motivated to contribute to all phases of a research project. The purpose of the recruitment position is for the candidate to achieve a PhD during the fellowship period
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addresses that challenge by developing a multimodal sensing and inference framework that can run on compact AI edge hardware while remaining reliable in complex, contested, or visually degraded environments
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methodologically challenging. In realistic applications, uncertainty arises from multiple sources, including parametric uncertainty, model-form and structural assumptions, numerical discretization, and incomplete