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Field
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Arabidopsis thaliana or other plants Documented applied skills in molecular biology techniques (cloning, transformation) Documented applied skills in plant cell imaging Documented training in Python and/or R
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educational system A scientific profile relevant for the nuclear medical applications research programme, as outlined above A solid background in scientific computing, including proficiency in Python
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programming (e.g., Python) Documented proficiency in deep learning frameworks (e.g., PyTorch) Documented background in machine learning, mathematics, linear algebra, and statistics Fluent oral and written
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the Norwegian educational system A solid background in machine learning, mathematics, linear algebra, and/or statistics is also required Solid knowledge and experience in Python programming is required Experience
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analysis Solid programming experience (e.g. Python, R, MATLAB, GAMS or similar) Interest in environmental risk, emissions analysis, and sustainability transitions. Ability to work both independently and
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: Valid driver’s license. Programming and numerical analysis skills (e.g., Python, MATLAB) and/or experience with groundwater/geochemical modelling software (e.g., MODFLOW, PHREEQC). Experience with
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spectroscopy is highly beneficial Experience with and knowledge of mathematical modeling techniques (numerical solution of Partial Differential Equations) Programming and data analysis in Python Language
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Equations) Programming and data analysis in Python Language requirement: Good oral and written communication skills in English English requirements for applicants from outside of EU/ EEA countries and
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in relevant genetic data analyses such as GCTA, polygenic scores, GWAS, or family genetic risk scores. Familiarity with R, Python, Julia, or other relevant computing languages. Experience with register
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. Desired qualifications: Strong theoretical and methodological capacities in statistics Documented expertise in computational methods and experience with R or Python programming Experience in Bayesian