937 developer-"https:" "https:" "https:" "https:" "https:" "https:" "https:" PhD scholarships
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on developing probabilistic latent-variable methods for large and structured biological data, with applications in genomics, spatial transcriptomics, and fluorescence imaging. High-dimensional and structured
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realistic oxide nanoparticles with sizes from a few 10s of atoms to several 1000s of atoms. In each case, machine learned interatomic potentials (MLIPs) will be developed to describe their structure and
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for 1.0 fte (38 h/week). You will have ample opportunities for further development of knowledge and technical and personal skills through courses at the Academy and (inter)national conferences. Where
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resources. This PhD will develop learning methods for coordinating such agentic systems under changing network conditions, incomplete information, and operational constraints. The research will build
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highly collaborative and friendly atmosphere, we will give you all the support you need to develop and grow. Moreover, as a valued member of the FNS consortium, you can collaborate with various partners in
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Ecology (NIOO-KNAW) and the department of Terrestrial Ecology can be found at the website: http://www.nioo.knaw.nl . More information about the Copernicus Institute of Sustainable Development can be found
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spatial and temporal variability in sediment accumulation and vegetation development. This PhD project is part of a larger interdisciplinary research initiative aiming to enable a transition towards more
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at the Ministry of Higher Education, Research, and Innovation (MESR). As part of the shift in the energy mix toward a reduction in the share of fossil fuels, the development of new stationary energy storage systems
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PhD candidate for the project "Modulation of inflammatory Dendritic cell subsets in atherosclerosis"
cellular therapy, provides a unique approach for the development of new therapies for the treatment or prevention of atherosclerosis. For more information, see https://www.universiteitleiden.nl/en/science
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£26,805 per year, and includes the PANDA DFA training programme as part of the 2026 Cohort (https://www.bangor.ac.uk/panda ). This project is linked to UK National Nuclear Laboratory (UKNNL), who will