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Field
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technical depth in NLP methods and a clear interest in problems related to AI safety. Minimum Qualifications: PhD in Computer Science, Information Science, Computational Linguistics, Machine Learning, or a
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Fellow to develop and evaluate artificial intelligence methods for physical medical procedures. The fellow will design and implement machine learning models to analyze procedural data, support clinical
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Fracture Network (DFN) and Embedded Discrete Fracture Modeling (EDFM) Tracer design and interpretation Machine learning or optimization for reservoir management Experience working with field-scale geothermal
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transportation contexts, and machine learning classifiers Heuristics & Solvers: Develop and refine custom heuristics and metaheuristics (e.g., Tabu Search, Genetic Algorithms) to find high-quality solutions
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UiO/Anders Lien 16th July 2026 Languages English English English PhD Research Fellow in AI for Rehabilitation and Motor Learning Apply for this job See advertisement About the position We invite
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supporting documentation, proven experience in all of the following areas: Computer vision and video processing (ingestion, ROI, 2D/3D keypoints, heatmaps); Deep learning and temporal modelling (CNNs
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will be preferred. Requirements: PhD degree in learning sciences, educational technology, human-computer interaction (HCI), information technology, AI or relevant fields Prior experience and proficiency
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of Oslo’s Department of Informatics (IFI) and is hosted by the Network and Distributed Systems Research Group (ND) with co-supervision from IFI’s Machine Learning section and the University of Inland
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analysis Machine learning and retrieval-augmented AI models for biomarker prioritization and decision support ·Work closely with cross-functional team members to develop hypotheses, interpret data, and
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neurocritical care research The Opportunity We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis