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for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation until 2033. The project PI and team are also in close collaboration with the Epigenomics of Breast Cancer
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researchers for work in higher academic positions within their disciplines. Your main tasks will be Develop and apply machine learning techniques and statistical analyses, including novel methodology
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studies. Proficiency in relevant computational tools and statistical methods. Experience with machine learning in large datasets. Interest and motivation to work in a multidisciplinary team. Ability to work
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the SFF Integreat, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation until 2033. The project PI and team are also in close collaboration
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science. The main purpose of the fellowship is to qualify researchers for work in higher academic positions within their disciplines. Your main tasks will be Develop and apply machine learning techniques and
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researchers for work in higher academic positions within their disciplines. The duration of appointment is 3 years. Your main tasks will be Develop and apply machine learning techniques and statistical analyses
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Develop and apply machine learning techniques and statistical analyses, including digital twin methodology, to fit and validate prediction model. Perform quality control and imputation of genotype and