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Postdoctoral Researcher in Innovation&Investment Policy for Hydrogen Clusters in the EU(0.8-1.0 fte)
Apply now The Department of Economics of Leiden Law School at Leiden University has a vacancy for a: Postdoctural Researcher in Innovation&Investment Policy for Hydrogen Clusters in the EU (0.8-1.0
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, and social networks, cluster within families, and how they, in combination with molecular profiles, relate to the physical living environment, health outcomes, and lifespan. This knowledge will then be
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labs for sample preparation. The group is part of a bigger research cluster focusing on optical sensing. The aim of the Ultrafast Dynamics in Nanoscale Systems group is to understand physical phenomena
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using a local high performance computing cluster. You will work closely with experts in ALS, bioinformatics, neuroscience and RNA biology. You will support in the supervision of more junior researchers
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labs for sample preparation. The group is part of a bigger research cluster focusing on optical sensing. The aim of the Ultrafast Dynamics in Nanoscale Systems group is to understand physical phenomena
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, linked to major study cohorts such as the LLS and LifeLines. The ultimate goal is to gain insight into how socioeconomic resources, such as income, education, and social networks, cluster within families
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Systems (IRIS) cluster at the Mathematics and Computer Science department. The research topic will be tailored to your research interests. The project offers collaboration with industrial partners
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performance of subsurface hydrogen storage. Analyse the simulation results to identify clusters of typical reservoir behaviours and link these clusters back to geological properties to understand (i) how we can
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clusters of typical reservoir behaviours and link these clusters back to geological properties to understand (i) how we can engineer the reservoir to maximise the performance of cyclic hydrogen storage and
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this project is how to effectively prioritize the millions of unknown biosynthetic gene clusters and metabolite features for the discovery of new antimicrobials through predicting structural and functional