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Field
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to: Develop mechanistic and data-driven models to analyse concentration–response relationships and biological readouts from advanced in vitro assays Apply statistical and computational methods to quantify
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include Luxembourg and its neighbour regions. Using an innovative multi-method design, the project integrates: Daily diary and ecological momentary assessment (EMA) approaches In-depth qualitative and
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interpreted. We are expanding our research group working on image-based methods for large‑scale biodiversity monitoring and invite applications from candidates eager to push the boundaries of automated
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effectively within interdisciplinary and multicultural research teams. We strongly encourage applications from computer scientists with substantial experience in deep learning and related methods, even if
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of the relationship between the characteristics of the roadside area and accident rates, in the development of new methods to support sustainable mobility and logistics, in the installation of sensors
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methods, including UAV-based landscape mapping, terrestrial and freshwater eDNA, passive acoustic and camera monitoring, and novel sensor and logger networks for real-time analysis of greenhouse gas
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aim is to understand how pharmacological agents affect fenestrations and the microvascular architecture of the liver. Our work also involves developing improved methods for isolating and culturing
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for talented, young researchers within the field of Pharmacoepidemiology as presented by Ass. Prof Trinh: My research interests focus on the application and development of methods to (1) analyze real-world data
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transcriptomic methods. The selected candidate will contribute to the part of the project focused on the functional studies of the identified proteins and pathways. Depending on their experience and research
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neuronal cultures and brain tissue samples will be used. Targeted identification will be achieved by e.g. cryo- immunofluorescence (cryo-CLEM) and immunogold. Cryogenic focused ion beam milling methods will