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performance in organic electronic and electrochemical devices. Multiscale simulation and integration of machine learning: Use molecular dynamics, quantum mechanical and continuum models, in combination with
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This PhD project focuses on strengthening network security for large-scale distributed AI training. As training increasingly spans multiple data centers connected over wide-area networks, it
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managing large amounts of data by designing structured databases (PostgreSQL, MySQL). Machine learning methods such deep learning for analysis of proteomics data and classification of cancer profiles. Since
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This PhD project focuses on advancing network security in the emerging Web3 ecosystem. As decentralized applications built on blockchain and distributed ledger technologies become more widespread
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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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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description The postdoctoral project is focused on development and the exploitation of machine learning tools to accelerate the analysis of microtomography data at the MAXIV synchrotron facility. MAXIV
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tasks Contract terms The PhD positions are fully funded from start. The position is limited to four years, with the possibility to teach up to 20%, which extends the position to five years. A starting
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advanced biostatistics/machine learning analyses, but also with other types of analysis. The work involves supporting Swedish researchers under a “user fee-based” support model. The projects will differ in
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if you have worked with prediction models, machine learning or AI models and are familiar with blood cells such as neutrophils, leukocytes and platelets. Work experience in the area is meritorious. If you