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Field
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: • Graph-based learning and community detection: Identify cohesive and antagonistic groups within signed networks. • Machine learning and network embeddings: Measure consensus, polarity, and opinion shifts
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on precision viticulture and related topics Analyse complex datasets using statistical and machine learning methods Publish in reputable national and international journals Collaborate with interdisciplinary
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of hire. MD or PhD. Research expertise in Ophthalmology, Biomedical Engineering, Computer Science, Data Science, Machine Learning One year’s work experience, or equivalent in thesis research and other
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. Coordinate modelling activities across multiple projects and deliver high-quality outputs on time. Integrate new methodologies, including AI and machine-learning approaches, into simulation design. Conduct
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large, highly diverse and multi-modal datasets (e.g., images, surveys, statistical and sensor data). Familiarity with geostatistical, GDAL, Python, PostGIS/PostgresSQL, Machine Learning, AI, Internet
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where AI systems are reshaping how we learn, work and participate in democracy, our centre tackles the promise and peril of hybrid intelligence—human and machine working and learning together. AI LEARN’s
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of subsurface processes. You will be responsible for leading the development of the approach, which could include transferring learning from other geographic regions and data types, machine learning methods
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technologies and machine learning; and interact with collaborators and team members Prepare data reports for weekly meeting with PI and bi-monthly reports for weekly lab meeting Attend educational activities
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bring expertise in computational methods (such as machine learning, chemo-informatics, molecular dynamics simulation, structural biology) and / or experimental methods (such as biophysical analysis
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in coding e.g. Python, or MATLAB Writing skills for research papers. Experience in applied machine learning, fault diagnosis, laboratory testing and development is a plus. Good knowledge in Norwegian