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Leibniz-Institute for Plant Genetics and Crop Plant Research | Neu Seeland, Brandenburg | Germany | 2 days ago
Training for Next Generation Scientists in Spatio-Temporal Imaging of Plant Cells” (AGILE) European project at the forefront of chromosome biology and microscopy (https://www.msca-agile.eu/ ) PhD Research
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contract is based on § 2 WissZeitVG. Your Tasks: Generative diffusion models (DMs) learn to reverse a diffusion process from an analytically known prior distribution to a target distribution that is inferred
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HBIGS Heidelberg Biosciences International Graduate School | Heidelberg, Baden W rttemberg | Germany | about 4 hours ago
30℃) conditions, using PHYB immunostaining, SABER-FISH labelling of PHYB target loci (S1), 3D STED imaging and available image analysis workflows2 (S2). (Obj2) We will measure the spatial distribution
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for distributing bigraphical world models using Conflict-free Replicated Data Types (Bigraph-CRDT) and to extend these methods for the general distribution of DT data, ensuring high availability and resilience
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research school on secure distributed computing (SeDiC) is proposed. SeDiC aims to tackle the challenges of exchanging and computing data across a network of interconnected systems. It addresses scalability
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Helmholtz-Zentrum für Infektionsforschung GmbH | Braunschweig, Niedersachsen | Germany | 20 days ago
climate,environmental, land-use and socio-economic drivers to predict vector distribution, transmission potential andoutbreak risk for pathogens such as West Nile fever,tick-borne infections and Aedes-borne
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Infrastructures Didactics of Informatics Digital Humanities Distributed Systems High-Performance Storage Machine Learning Medical Informatics Neural Data Science Practical Informatics Scientific Information
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candidate to investigate how pathogens and antimicrobial resistance (AMR) genes are distributed via dust particles in and around agricultural facilities. This interdisciplinary project is conducted in close
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project, you will help design, simulate, and optimize these next-generation communities — making clean, local, and intelligent energy systems a practical reality. Your key responsibilities include
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(4DSTEM). This approach will combine three-dimensional charge distribution data, generated through atomistic simulations, with machine-learning-driven modelling to guide and refine the phase reconstruction