391 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "FORTH" research jobs in Norway
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the project lead if you have further questions about the project. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/293031/postdoctoral-research-fellow-in-studying-the-role
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acquire such competence during the employment period. In such cases, you will also be assigned relevant teaching as part of the career-promoting work. The appointment is to be made in accordance with NTNUs
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samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue samples. Apply the developed
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. Strong (inter-)national network in field of application. Experience with high-performance computing (HPC) and large datasets. Experience with machine learning applied to geophysical signals. Experience in
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. The project is conducted in close collaboration with the SFF Integreat, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation until 2033
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research in various areas of mobile network systems, multimedia and AR/VR/XR systems, robotics and machine learning, focusing on fundamental aspects as well as on applications in multidisciplinary contexts
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language processing or computational linguistics; alternatively, in computer science or machine learning with a specialization in natural language processing Documented knowledge of core machine learning methods and
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Care without Harm and the Norwegian Bioart Arena. The Postdoc will also contribute to other project-related tasks and activities. For more information and how to apply: https://www.jobbnorge.no/en
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Value conflicts and tensions in the life sciences and its different epistemic cultures and evaluative principles and practices. For more information and how to apply: https://www.jobbnorge.no/en/available
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to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide