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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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Science) in a uniquely interdisciplinary environment. The project will be supervised primarily by Professor Anagha Madhusudan Joshi-Michoel, who specializes in applying machine learning and data science
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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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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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under the “Cryptographic elements of trustworthy AI” project. The main research objectives for the project are the following: Analyze security of Machine Learning (ML) models against data modifications
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. Experience with AI-related research and/or innovation is an advantage. Experience in machine learning is a requirement. Experience with programming and app development will be emphasized The LEAD AI mobility
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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 able to work independently and in a
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qualifications are desirable: The successful applicant should have experience in large-scale phenome and genome-wide association studies, r and python programming languages, causal inference analyses and machine
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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
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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 AI fellowship