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samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue samples. Apply the developed
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learning and statistics, and who are eager to contribute to impactful methods for generating private and fair synthetic data with good utility. This project involves development of deep learning based
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communication skills in English 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
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with the centre’s user partner Kongsberg Satellite Services (KSAT). We are therefore seeking someone with a strong interest and competence in deep learning. Working environment: The project will be done
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application development experience Maritime operational knowledge & experiences. Large Language Model-based application development. Deep Learning techniques, Data Engineering, and Semantic Technologies Open
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or a Scandinavian language is also beneficial. The following are considered beneficial: solid theoretical background in robot perception and navigation deep foundation in modern machine learning solid
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: Experience with deep learning frameworks like PyTorch Experience in LLM development and/or evaluation Language requirement: Good oral and written communication skills in English English requirements
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functions to work properly. Please turn on JavaScript in your browser and try again. UiO/Anders Lien 1st March 2026 Languages English English English PhD Research Fellow in Machine Learning for Cognitive
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application development. Deep Learning techniques, Data Engineering, and Semantic Technologies Open-source artificial intelligence, machine learning, statistical estimation methods, software tools, and big-data
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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