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world 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
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Professional qualifications (required) Relevant PhD degree (e.g. computer science, machine learning, statistics) Experience in developing deep learning models for 3D point cloud data Strong programming skills
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, grid computing and physics data analysis, machine learning, and interactive and collaborative systems. The prospective PhD candidate will work in close cooperation with our current PhD students in
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the Job related to staff position within a Research Infrastructure? No Offer Description The position is in the Digital Signal Processing and Image Analysis (DSB) research group, Section for Machine
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that specifies the competencies that the Research Fellow will acquire. Access to career guidance will be provided throughout the doctoral education. Research topic Over the past years, University of Stavanger has
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for forest applications Good presentation skills, written and oral Qualifications that will be emphasized Experience from research in boreal forest ecosystems Programming skills Experience with machine
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on characterizing forest structure and biodiversity via Unsplash Professional qualifications (required) Master’s degree in machine learning, computer science, or a forest-related field with a focus on remote sensing
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programming and computational models that can genuinely outperform classical computing systems. However, this also presents major challenges for the future of quantum machines, making it a critical research
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for imaging Apply for this job See advertisement About the position Position as PhD Research Fellow in machine learning available at Department for Informatics with the research group Digital Signal Processing
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engineering (elkraft). Experience in cybersecurity incident management. Experience in machine learning/artificial intelligence methods. Experience in simulation and modeling. Applicants will be assessed