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research questions, and a contract extension and/or PhD opportunity is desired (subject to successful third-party funding). Job responsibilities Main tasks will be the curation and analysis of large-scale
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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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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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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
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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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. The position The successful candidate is expected to work closely with the LoCiS PI, Professor Rubina Raja, on a number of tasks, including: Supporting large research/publication projects (including copyediting
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to support decision-making by integrating physical models and sensor data. These methods are validated through industrial case studies, with a particular emphasis on critical infrastructures where complexity
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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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Foundation RECRUIT grant ("Data Management, Algorithms, & Machine Learning for Emerging Problems in Large Networks – with Interdisciplinary Applications in Life & Health Sciences". NNF22OC0072415