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well as for validation of numerical simulation results. As part of the work task, we expect machine learning to be employed to improve accuracy and efficiency of numerical methods, combining advanced technology with
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, we expect machine learning to be employed to improve accuracy and efficiency of numerical methods, combining advanced technology with scientific research. About the Department of Mathematics at UiB
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at https://cbu.w.uib.no/joshi-group/ . Co-supervisors include experts in machine learning and AI, Pekka Parviainen and Tom Michoel, alongside leading epidemiologists, Tone Bjørge and Kari Klungsøyr. The core
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Joshi-Michoel, who specializes in applying machine learning and data science approaches to understand human health and disease, with a particular focus on women's health, the project aims to contribute
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important for renewable energy production and production variability will be an advantage. Knowledge of machine learning or optimization will be an advantage. Applicants must be able to work independently and
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. Knowledge of machine learning or optimization will be an advantage. Applicants must be able to work independently and in a structured manner and demonstrate good collaborative skills. Applicants must be
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UNIX/Linux interface and basic programming (e.g. Python) is a requirement. Experience with machine learning is an advantage. Experience from free energy calculations is an advantage. Applicants must be
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be employed by any other institution for the time of the fellowship. Experience with AI-related research and/or innovation is an advantage. Experience in machine learning is a requirement. Experience
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and they cannot be employed by any other institution for the time of the fellowship. Experience with AI-related research and/or innovation is an advantage. Experience in machine learning is a
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Conserved Binding Sites: A Case Study Using N-Myristoyltransferases as a Model System. J Med Chem. 2020). The lessons learned from the validation shall also be used to develop improved methods. About the LEAD