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of samples. To apply and further optimize data analytical workflows. A comprehensive database will be created, documenting the key chemical and physical properties of advanced bio-oils. The qualified applicant
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demonstrating how predictive analytics can improve maintenance and production planning. By comparing data-driven and traditional methods, the project will highlight the tangible benefits of digital platforms
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focus is demonstrating how predictive analytics can improve maintenance and production planning. By comparing data-driven and traditional methods, the project will highlight the tangible benefits
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in the Danish energy sector. As a PhD candidate, you will join the Energy Markets and Analytics (EMA) Section within the Division for Power and Energy Systems (PES). The EMA Section is renowned for its
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be important. You are expected to actively contribute to joint research projects, experimental design, and data interpretation across disciplinary boundaries. Responsibilities and qualifications Your
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Engineering, respectively, will be important. You are expected to actively contribute to joint research projects, experimental design, and data interpretation across disciplinary boundaries. Responsibilities
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on enzyme kinetics and stability measurements. The team have access to labs equipped with alternative reactors and excellent analytical equipment. Responsibilities and qualifications The position includes
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English (both oral and written), have good academic writing and presentation skills. Competences in analytical chemistry, photochemistry, and modelling of chemical processes are expected. Experience with
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Science, e.g., Molecular Biology. Expertise in functional genomics approaches and computational data analysis. Expertise and interest in gene-regulatory mechanisms. Motivation and strong analytical and
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project, co-funded by the Innovation Fund Denmark and the Department of Management, Aarhus BSS, Aarhus University. Candidate profile We are seeking applicants with strong knowledge of data analytics and