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and the national infrastructure NorHTE, which is under establishment, to optimize synthetic steps (and routes) using machine learning in closed-loop (autonomous) optimizations and for parallel synthesis
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flexibility. We plan to use the departments laboratory for automated chemistry and the national infrastructure NorHTE, which is under establishment, to optimize synthetic steps (and routes) using machine
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requirement Experience with data analysis and machine learning models is an advantage Experience from molecular modelling or molecular dynamics simulations is an advantage Applicants must be able to work
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employment that the master's degree has been awarded. Experience from protein bioinformatics is a requirement Good programming skills are a requirement Experience with data analysis and machine learning models
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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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, 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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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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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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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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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