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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
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at Stockholm University. We have a strong tradition in sampling but areas that we are growing in include, but are not limited to, Bayesian inference, the intersection of statistics and machine learning
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to investigate flow-induced forces in hydraulic turbines under varying operational conditions and how these forces affect the degradation and lifetime of the machines. About the position The position is based
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of mathematical areas. The position will be placed at the Department of Computer Vision and Machine Learning (CVML) at the Mathematics Centre (https://maths.lu.se/). Mathematics Centre is a department
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application! Work assignments Our research projects focus on distributed sensing, hardware-efficient signal processing, robustness and resilience, and communication-efficient decentralized machine learning
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The postdoc fellow will conduct research in the intersection of AI/Machine Learning and Software Technology. The advertised position will be placed in the DISTA research group (https://lnu.se/en/dista
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on how your research can be further developed into innovations. You are interested in driving the integration of methods in artificial intelligence (AI) and machine learning (ML) to improve and optimize
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focuses on the creation of visual representations that create insights and clarification of complex data. This includes the interpretability and explainability of machine learning models
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or explainable AI or safety). Experience in machine learning, causal inference, image processing, human-robot interaction, or large language models. Experience in analyzing multimodal data (e.g., text, sensor