322 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" Fellowship positions in Norway
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profile for their ideal candidates are described as follows. PREMAL is a project focused on privacy-preserving machine learning using FHE. The project will investigate trade-offs between accuracy, time, and
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numerical models and machine learning tools to predict loads, assess structural responses, and identify damage under extreme conditions. By combining computational simulations with data-driven approaches
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Sciences, Department of Teacher Eduaction and School Research PhD Research Fellow in Education: Learning, Reading, and Assessment in the Context of Generative AI Apply for this job See advertisement Job
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publications and to contribute to a rapidly evolving field. For more information and how to apply: Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/295728/postdoctoral-research-fel
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PhD Research Fellow in Education: Learning, Readning, and Assessment in the Context of Generative AI
Sciences, Department of Teacher Eduaction and School Research PhD Research Fellow in Education: Learning, Readning, and Assessment in the Context of Generative AI Apply for this job See advertisement Job
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, the Hospital Pharmacies Enterprise in South-Eastern Norway and the Medicines Optimization Innovation Centre, Nord-Irland. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job
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of these groups is invited for an interview as part of our commitment to inclusivity and equal opportunity. For further information about the recruitment process, click here . Where to apply Website https
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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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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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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