14 machine-learning-"https:" "https:" "https:" "https:" Fellowship positions at University of Oslo
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«Detaljer» for å lese mer om dette og tilpasse dine valg. Om cookies Bare nødvendige cookies UiO/Anders Lien 9th September 2026 Languages English English English PhD Research Fellow in Machine Learning for
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candidate will develop and apply cutting-edge remote sensing or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via cryospheric models
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– Discovering Rare Proteins Across the smORF Landscape See advertisement About the position Would you like to use large-scale data analysis and machine learning to uncover proteins that conventional
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«Detaljer» for å lese mer om dette og tilpasse dine valg. Om cookies Bare nødvendige cookies UiO/Anders Lien 16th October 2026 Languages English English English PhD Research Fellow in Machine Learning and
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fellowships in machine learning await. Collaborate, innovate, and thrive! PhD Fellowships in Knowledge-Driven Machine Learning in Norway (8 positions) Apply for this job See advertisement About the positions
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Informatics, in the Scientific Computing and Machine Learning (SCML) research group. Starting date as soon as possible/by agreement. The fellowship period is three (3) years. Depending on the
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to develop a biophysically interpretable machine learning model that integrates diverse biological data—including transcription factor (TF)–DNA interactions, epigenetic features, and three-dimensional
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as machine learning and data assimilation via cryospheric models. A main focus of this work is snow and glaciers in the mountains around the globe. Candidates with relevant prior research experience
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quantitative analyses or game theoretic analysis. Experience with large language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. The evaluation of
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language models, machine learning, and/or programming in R or equivalent programs is an advantage but not a requirement. The evaluation of applicants primarily hinges on their documented academic