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theory and digital twins, and the Data and Knowledge Management (DKM) research group, which works in sematic technologies. Both groups have a dynamic and interactive working environment with good gender
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: The topic of the Master’s degree must be of relevance to the job description Preference will be given to candidates with a multi-disciplinary background consisting of both control theory (or related fields
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Systems (PSY) research group, which works in formal methods, programming language theory and digital twins, and the Data and Knowledge Management (DKM) research group, which works in sematic technologies
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. Qualification requirements: Applicants must hold a degree equivalent to a Norwegian doctoral degree in Statistics or a closely related field with a documented competence in statistical theory and methods
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underpinned by similar genetic mechanisms in distantly related plant species. The candidate will compare population-level genomic data from different Arctic taxa, conduct controlled common garden experiments
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modelling, and artificial intelligence. The postdoc will contribute to both the theoretical and applied dimensions of the IMF initiative and is expected to: Investigate how logical and philosophical theories
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Integreat develop theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data. By combining the mathematical and computational cultures, and the methodologies
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a documented competence in statistical theory and methods. Doctoral dissertation must be submitted for evaluation by the closing date. Only applicants with an approved doctoral thesis and public
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consisting of both control theory (or related fields) and economics (or related fields). Applicants must have experience in one or more of the topics: Model-predictive control Numerical optimization
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at Integreat - Norwegian Centre for Knowledge-driven Machine Learning is a Centre of Excellence, funded by the Research Council of Norway. Researchers at Integreat develop theories, methods, models, and