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within a Research Infrastructure? No Offer Description Doctoral researcher in choline research – part of a MSCA Doctoral Network on micronutrients in sustainable and nutritious diet Department of Food and
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measurements at 18-digit accuracy using an optical clock network. Nature 591, 564–569 (2021). https://doi.org/10.1038/s41586-021-03253-4 [2] Chave, A. D. (2019). A multitaper spectral estimator for time-series
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Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
with word embeddings, semantic modelling, and/or network analysis Ability to work independently as well as collaboratively in an interdisciplinary environment Excellent written and spoken English
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, resilient networking and fault-tolerant systems (detection, isolation, recovery). Proficiency in Python for rapid prototyping, data analysis, and simulation (e.g., NetworkX, numerical optimization, agent
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required to carry out research activities in various areas. On the theoretical side, they will contribute to the development of methodologies for the analysis of complex networks with applications
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European wide Doctoral network on the security and resilience of critical cyber physical systems – SecReSy4You, funded by the Marie Skłodowska-Curie Actions Doctoral Networks scheme (https://secresy4you.eu
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investigate deep learning architectures capable of learning microstructure-property mappings, including convolutional neural networks for microstructure image analysis, graph-based representations
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Horizon Europe MSCA Doctoral Network, SUPER, as a PhD Fellow. The successful candidate will be registered as a fee free PhD student at Universidad Europea de Madrid and enrolled in the SUPER Doctoral
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Zeppelin airship Apply advanced data analysis methods, including statistical tools and programming, to large multidimensional datasets from chamber and airborne experiments Present your results
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real-world field data. The central research question of this thesis is: How can Extreme Value Theory (EVT) and Bayesian Networks (BN) be coupled to build a predictive and dynamic model of NaTech risk