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, reliability, cost-effectiveness, and sustainability across applications. In parallel, we advance microgrid technologies, supporting developing countries in achieving climate neutrality by integrating
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-based surrogate models. Experience with high-performance and parallel computing. Familiarity with digital twins and real-time deployment of predictive models is an advantage. Who we are The two
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, analytical measurements, data processing, and collaboration with researchers and project partners across the value chain. We are looking for a candidate with a background in biotechnology, environmental
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, alternative fragmentation techniques, novel sample processing technologies, or integrated analytical workflows. Expertise in one of these areas is sufficient. Applicants are not expected to possess
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, working with quarto documents, visualizing data, and writing clean & reproducible code) Experience with natural language processing tasks (in R or Python - familiarity with common tasks such as sentiment
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-genome sequencing and resequencing data from non-model arthropods, particularly insects and spiders. A substantial part of the work will involve processing and analyzing genomic data from historical
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the Department of Ecoscience (AU Ecoscience - Marine Mammal Research) and under the supervision of Senior Scientist Frants Havmand Jensen ( https://frantsjensen.weebly.com/ ). The unit conducts
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: Support with handling, analysis, and processing of ecological data, including geospatial, remote sensing, genetic and other data Retrieval, integration, management, and archiving research data in line
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acquisition. • Must have proven scientific competences within agricultural engineering, automation, signal processing, as well as data processing and interpretation. • Experience with acquisition of
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associated thermodynamic calculations Experience with microbial inhibition models Model-based data processing Excellence in both written and spoken English You will be working in the research group