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Exoplanet Group at DTU Space. At DTU Space, you will have access to data from world-class telescopes, including JWST, ultra-precise RV spectrographs (e.g., HARPS-N and EXPRES), and access to ESO facilities
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analytical methods to large data sets The possibility for contract extension Flexibility in planning working hours Advanced professional training opportunities Possibility of participation in international
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Post Doctoral Researcher in Human-centred Large Language Models for Software Engineering, Departm...
. Required qualifications: A Ph.D. degree in Computer Science, Data Science, Software Engineering or related field. Solid research experience with using Large Language Models. Solid programming expertise in
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these new large-scale data sources to develop new approaches for analysis of microbial horizontal gene transfer using long-read metagenomics in complex environments. The postdoc will be part of the Microbial
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and applying genetic and genomic approaches to biodiversity research. This includes integrating environmental DNA (eDNA) and molecular tools with ecological data to enhance our ability to assess
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of cellular aging, resilience, and fibrosis. Responsibilities Develop and implement analytical pipelines for large-scale single-cell, spatial, and multi-omics data integration Build and apply machine learning
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laboratory imaging techniques on PV modules to large scale field inspections. You will contribute to the development of daylight electroluminescence and photoluminescence inspections together with data-driven
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medicine. The Department of Biomedicine provides research-based teaching of the highest quality and is responsible for a large part of the medical degree programme. Academic staff contribute to the teaching
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sensing and responding to the chemical landscape surrounding them as well as the chemical signals inside of them. This project is devoted to gather large data sets to investigate links in olfactory receptor
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environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental sustainability. You will focus on processing