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important to integrate knowledge on processes of cognitive change and updates among individuals and in interaction with others into our data-driven computational modelling in order to understand broader
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PostDoc in aerobiological modelling Are you interested in atmospheric science and can you contribute to the development of a new generation of numerical models describing concentrations and
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. The work combines physics-based thermal design and process-level system simulation with high-fidelity computational fluid dynamics and fast reduced-order and machine-learning models, so that the final design
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motivated by combining rigorous modelling with direct industrial impact in the green transition. You have: A PhD in chemical engineering, process engineering, mechanical engineering, data science, computer
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in materials synthesis, advanced scattering and spectroscopy, electron microscopy, solid-state NMR, electrochemistry, property measurements and computational modelling. Its research spans battery
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grant project “Driving innovation in crop resilience through Comparative QTLomics.” The selected candidate will contribute to five main objectives: 1. Apply large language models (LLMs) to collect
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models. However, rigorous methods for evaluating XAI algorithms are currently lacking. This is in large part due to a gap between how explainability is evaluated within computer science and philosophy. In
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Do you enjoy finding solutions to integrate and analyse large data sets of biodiversity dynamics and their drivers? Are you creative and able to couple various data flows and integrated modelling
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perturbation experiments to understand how cell type-specific epigenomes emerge during mammalian development, using gastruloids as an in vitro differentiation model. We aim for an open and collaborative work
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soon as possible thereafter. The position is a fixed-term full-time position for 3 years. Department of Clinical Medicine, Section for Bioinformatics and Computational Biology As a Postdoc at the