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be funded within the project titled ”A Probabilistic Inverse Model for Identifying the Source of Atmospheric Contamination on a Continental Scale” funding under the prestigious SONATA 20 competition
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The Postdoctoral Researcher will join a new interdisciplinary project developing an AI-augmented decision science platform to understand and model high-stakes human judgments. This position will be jointly mentored
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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. The iPSC lines we use are derived from patients or isogenic lines in which we induced disease-associated variants using CRISPR-Cas9. The iPSC-based models we have in the lab range from 2D cultures containing
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funded by UKRI and is fixed-term to 31 December 2026. This is an on-site position only. The project aims to develop a computational model for biodegradable polymers degrading in water under mechanical
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. The successful candidate should have expertise and experience in process modeling, techno-economic analysis (TEA) and life cycle analysis (LCA) of lithium-ion batteries and/or recycling and resources to products
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Machine System for Data Quality, our research goal is to create fully automated processes for all phases of the data life cycle. We seek a Postdoctoral Fellow with expertise in Large Language Models (LLMs
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-atmosphere dynamics. We will build an AI-enabled modeling system that couples a GPU-optimized ocean model with a biogeochemical module and AI-based, kilometer-scale atmospheric forecasts. This system will
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applied research to support the sustainable management of freshwater ecosystems. We require a quantitative ecologist with skills/experience in statistical and quantitative modelling. The successful
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, enabling systematic and efficient exploration using modeling and simulation tools.For the full details please check: https://workingat.vu.nl/vacancies/phd-in-reconfigurable-spatial-accelerators