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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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estimators, or machine learning) or other advanced statistical modelling. Advanced programming skills in Stata, R, Python or a similar software. Strong academic background with publications in international
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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
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variables, fixed effects for panel data, matching estimators, or machine learning) or other advanced statistical modelling.- Advanced programming skills in Stata, R, Python or a similar software.- Strong
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the postdoctoral program and together with you we will prepare a career plan, which contains the skills and knowledge you will acquire Open and inclusive working environment with committed colleagues Favourable
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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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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