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Field
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compression testing UV–Vis spectroscopy Surface profilometry Optical microscopy Scanning electron microscopy (SEM) Experience using or working with machine learning / AI approaches for materials development
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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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to the project’s scope, such as mechanistic interpretability of LLMs, robustness verification of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research
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to the project. Job Requirements: PhD degree in Computer Science, Electrical and Electronic Engineering, or related field. Min 3 years of relevant experience in computer vision, artificial intelligence, etc
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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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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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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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tissue specimens Assemble analysis pipelines using machine learning to process tissue data reproducibly and at scale Conduct analyses using programming languages such as R and Python Collaborate with other
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for an exception to this work arrangement. To learn more, please contact the hiring team, using the contact information below. While the official location of work for this position will be an NRC facility within
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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