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the broader area of Machine Learning, including Natural Language Processing and Web & Information Retrieval. According to CSRankings , the section has consistently ranked among the top research environments in
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new theoretical approaches for understanding stability, generalization, and feature learning in large-scale neural networks. Further details and application instructions are available at: https
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modelling. Experience with machine learning, prediction modelling, causal inference, or the integration of multiple data sources is an advantage. Excellent oral and written communication skills in English
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. This includes the use of Machine Learning (ML) and Artificial Intelligence (AI) methods. Project description The PhD project will be focused on developing, assessing, and comparing traditional and modern ML and
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quantitative field. Good scientific programming skills, particularly in Python, are required. Experience with atmospheric dynamics, numerical modelling, machine learning, or large meteorological datasets would
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for probabilistic unsupervised learning for structured biological data. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/307053/3-years-phd-position-in-probabilistic-machine
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of response and develop predictive models. The work will involve analysis of large-scale datasets through multiomics integration, machine learning, statistical genetics, QTL analysis and development of genetic
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-temporal-resolution bulk measurements (XAS, Raman spectroscopy, XRD), with particular emphasis on pair distribution function (PDF) analysis. Machine learning approaches will be used to support these analyses
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analysis, or assistive technology; Experience in applying AI methods such as machine learning, deep learning, computer vision, multimodal data analysis and large language models (LLM) in health-related
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welcomed. The project sits at the intersection of statistical genetics, systems biology, and machine learning, with strong emphasis on methodological development. Tasks of the PhD Student - Develop and