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qualifications PhD within forest sciences or statistics. Competence in forestry and model-based inference for forest inventory applications. Competence in DA. Experience in use of remotely sensed data for forest
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interaction processes and mineralogy or Physical and/or chemical planet formation processes Experience with numerical modelling of the relevant processes Interest in exploring statistical or machine-learning
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interaction processes and mineralogy or Physical and/or chemical planet formation processes Experience with numerical modelling of the relevant processes Interest in exploring statistical or machine-learning
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equivalent to a Norwegian doctoral degree in astronomy, physics, statistics, informatics or related topics. Candidates are encouraged to apply before the completion of their PhD degree, as long as their
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must hold a degree equivalent to a Norwegian doctoral degree in astronomy, physics, statistics, informatics or related topics. Candidates are encouraged to apply before the completion of their PhD degree
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on the expertise of the seven research groups involved, using a combination of experiments in cellular and animal model systems, mathematical modelling, machine learning and music technology. One PhD student
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on the expertise of the seven research groups involved, using a combination of experiments in cellular and animal model systems, mathematical modelling, machine learning and music technology. One PhD student
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methods and statistical analysis as well as routine documentation with GitHub Demonstrated knowledge on ‘omics` laboratory methods Experience working with biological oceanographic methods (primary
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methods and statistical analysis as well as routine documentation with GitHub Demonstrated knowledge on ‘omics` laboratory methods Experience working with biological oceanographic methods (primary
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to the problem and detailed implementation, but the results are expected to be published in scientific journals. Qualifications You must hold a completed PhD in Physical Oceanography, or other relevant sciences