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advances in our group, including new methods for detecting learning signals in linear networks that reveal aspects of the tasks they have learned, provide a powerful conceptual starting point. The scope
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, or materials informatics. Familiarity with explainable AI or counterfactual explanation methods. Experience with molecular dynamics data, graph neural networks, or multi-component system modelling. Track record
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researchers and practitioners in fields such as economics and engineering to solve complex problems significantly faster. Where to apply Website https://www.academictransfer.com/en/jobs/358369/postdoc-in
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, PlasmaObs, LCRS, Moonlight and Henon. You are encouraged to visit the ESA website: https://www.esa.int/ Field(s) of activity/research for the traineeship Many challenges and trends will affect the operations
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those skills to complex cultural questions. The fulltime position is for 18 months, starting May 1st, 2026. The project is funded by CLICKNL. What are you going to do Construct and analyze longitudinal
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to ESA’s strategy; a wide network of relationships and collaboration with top academics, industry and research centres; the opportunity to contribute to the Φ-lab strategy and activities. As an internal
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the local electricity system, while acquiring academic perspectives? Information This position is dual fold and has both a teaching and a research related aspect. Power networks are critical
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stakeholders, including conducting a Delphi study to establish shared principles and system boundaries; analysing and interpreting existing LCA, HTA and healthcare datasets, translating complex data
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to advance the resiliency and reliability of beyond-5G/6G networks. The candidate is expected to work on the European project PHRESH (https://itea4.org/index.php/project/phresh.html ) and the Dutch National
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(Faculty of Civil Engineering and Geosciences) and work closely with Dr Louise Nuijens and an (inter)national network of collaborators. QUASI offers a unique opportunity to combine cutting edge observations