508 data-"https:"-"https:"-"https:"-"https:"-"UNIVERSITY-OF-RIJEKA" positions in Denmark
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the EuroTeQ initiative at DTU by assisting with communication, event coordination, and data analysis related to student engagement and EuroTeQ educational offerings. The role involves collaboration with
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Postdoc – Performance requirements for biobased construction materials used in the building envelope
to ensure moisture-robust designs. In addition, competencies in data processing and integration, assessment criteria development, and practical construction knowledge are necessary to translate research
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training pipelines using modern ML frameworks Generating data on miBd–pMHC interactions to guide iterative model optimization, espeicially for specificity Benchmarking AI-designed recognition modules against
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sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe in encouraging inclusion, acceptance, and understanding by
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researcher network. The department consists of nine research sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe
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sensing and autonomous systems into geospatial analysis? Do you thrive in interdisciplinary environments and enjoy combining data-driven research with hands-on fieldwork — whether on boats, underwater
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, organoid-based models and in vivo cancer and infection models Integration and analysis of transcriptomics and proteomics datasets Establishment and maintenance of standardised experimental pipelines Data
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. You will also spend 3 months at Georgia Tech/Emory University (USA), working on machine learning and data benchmarking. Work description The selected PhD student will be responsible for the full
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sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe in encouraging inclusion, acceptance, and understanding by
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will be part of a research environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental