227 machine-learning "https:" "https:" "https:" "https:" "https:" "The University of Edinburgh" Fellowship positions at University of Oslo
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of partial differential equations (PDE). Examples of models in the scope of the project include particle models, stochastic PDE and models from fluid dynamics and machine learning. What skills are important in
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Machine Learning. We are looking for a motivated candidate, who has interest in both theoretical, methodological and applied research in anomaly detection in sequential data settings, and who is excited
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registries, advanced analytical methods, and clinical trial data to inform regulatory decisions, clinical practice, and public health. Read more about UIO:RWE here: https://www.uio.no/english/research
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English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements
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of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements: The norm is as follows: The average grade point
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(UiO). Learn more about working at PROMENTA here: https://www.sv.uio.no/promenta/english/ . Colourbox via Unsplash Colourbox Qualifications Required qualifications A PhD degree in psychology, human
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Language requirement: Fluent oral and written communication skills in English English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no
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plus Language requirement: Good oral and written communication skills in English English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https
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exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements: The norm is as follows: The average grade point for courses included in
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topics include (a) AI, machine learning, and large language models for measurement challenges (e.g., for small-sample calibration or for accelerated algorithms), (b) identifying and investigating aberrant