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in a PhD thesis submitted to the University of Oslo. We seek a highly motivated candidate with a strong background in molecular biology, human genetics/genomics, data mining, machine learning, and
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or connectivity analysis; machine-learning or deep-learning methods for geospatial analyses; ecological or remote-sensing fieldwork, particularly in alpine environments; Google Earth Engine, geodatabases or cloud
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28th October 2026 Languages English English English PhD Research Fellow in Learning-based Control of Autonomous Robot Manipulation Apply for this job See advertisement About the position A fixed
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warmer and wetter world. RAPTURE brings together high resolution physical simulations, machine-learning climate emulators, and new perspectives on the dynamics of weather and climate to understand i) what
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or human-computer interactions studies. The focus of the PhD-thesis needs to contain knowledge areas such as learning theory, cognitive theories with applications on studies of learning, design of learning
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on addressing this question which lies at the heart of understanding high-impact flooding in an ever warmer and wetter world. RAPTURE brings together high resolution physical simulations, machine-learning climate
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, Julia, C/C++ or similar is required. Experience with machine learning, analysis of climate or high-resolution model output, climate predictions/projections or environmental risk assessment is an advantage
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. Qualifications and personal qualities: Applicants must hold a PhD or equivalent doctoral degree within atmospheric physics, meteorology, climate science or machine learning. PhD-students may apply if defence of
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interpretable machine learning framework that integrates diverse biological data—including transcription factor (TF)–DNA interactions, epigenomic features, and three-dimensional (3D) genome organization
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applications for a PhD Research Fellow position in fairness in artificial intelligence, available at the Department of Informatics, in the Scientific Computing and Machine Learning (SCML) research group