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environmental factors such as fluctuating wind speeds and saltwater exposure. Using advanced statistical and machine learning techniques, including Bayesian inference and stochastic modelling, the project will
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assessment to support our growing portfolio of research activities. You will carry out various project-related tasks including economic impact assessment, method development and application, and statistical
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within DanSIC and CIMP. Collaborate with internal and external researchers to design experiments and analyze complex datasets. Perform statistical analyses and data visualization to interpret and publish
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competences in the Data Science and Statistics section, and who can contribute to the department’s strategic development in data science, artificial intelligence, and related topics. We are particularly, but
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funded by a major research project from the Novo Nordisk Foundation (NNF). The successful applicants would become part of the Data Science & Statistics section at the department. The successful candidate
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CFD workflows and Lagrangian particle/cell tracking to extracting actionable insights with statistical learning and AI/ML—ultimately enabling more robust scale‑up, smarter process control, and faster
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(programming, digital signal processing, modelling, statistics) is sought. The project involves collaboration with Prof. Marco Steinhauser (University of Eichstätt-Ingolstadt, Germany) and Dr. Ramakrishna
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statistical and machine learning techniques, including Bayesian inference and stochastic modelling, the project will quantify and analyse uncertainties in the design and operational performance
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of memory narratives. Perform data analysis using statistical software such as R and SPSS. Contribute critically to academic writing and the publication process. Take part in the center’s research events
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(programming, digital signal processing, statistics) is sought. Qualifications Ideally, applicants for the position should satisfy the following requirements: PhD degree in psychology, cognitive (neuro)science