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generated synthetic representations. The project will also explore machine-learning approaches and efficient imaging strategies, including reconstruction of three-dimensional pore structures from radiography
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representations. The project will also explore machine-learning approaches and efficient imaging strategies, including reconstruction of three-dimensional pore structures from radiography. By linking defect
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years with research duties exclusively,. A career plan will be prepared that specifies the competencies that the Research Fellow will acquire. Access to career guidance will be provided throughout
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Is the Job related to staff position within a Research Infrastructure? No Offer Description You are keen on contributing to new advances in deep learning methodology for imaging for monitoring marine
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four years are expected to acquire basic pedagogical competency during their fellowship period within the duty component of 25 %. Project description and work tasks Particle accelerators are engines
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: Preference Learning for LLMs Apply for this job See advertisement About the position Integreat – the Norwegian Centre for Knowledge-driven Machine Learning at the University of Oslo – invites applications
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of the researchers of the DKM group are also affiliated with the Norwegian Centre for Knowledge-driven Machine Learning (Integreat) . The candidate is expected to join Integreat and strengthen the interdisciplinary
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working with machine learning techniques to develop emulators for the theoretical predictions of various observables as function of cosmological parameters. The candidate will develop and use skills in
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machine learning methods and apply them in an interdisciplinary research environment spanning physics, neuroscience and computational science. You will be expected to participate both in the activities
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position as Postdoctoral Fellow in law at the UiS School of Business and Law, Department of Accounting and Law. The Postdoctoral Fellow will be affiliated with the research project AUTO-MARE – Autonomous