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public audiences and taking part in a pilot programme where experience can be acquired in high school science teaching; use graph theoretical tools to develop new fundamental frameworks and analytic tools
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you eager to make AI more sustainable? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase
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co-design adapted and new methods to enhance reflection and learning in and adaptive capacity of learning-oriented experiments. The intended start date of your employment is 1 November 2025 and the
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comfortable applying analytical thinking to explore research questions and have programming experience (preferably in Python). You have an affinity with coastal numerical modelling, e.g. AeoLiS, XBeach
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of the Dutch NWA consortium “PRELIFE”, https://www.originscenter.nl/prelife/ The origin of life remains one of science’s most profound and enduring mysteries. Despite numerous theories, no single explanation has
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sources. Such modelling provides essential tools for designing low-carbon, efficient, and adaptive energy infrastructures at local level. By leveraging data-driven methods, cities can devise strategies
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technology, which works by cutting a DNA sequence at a specific genome location and deleting or inserting genes there. The CRISPR-Cas method provides an excellent basis for the development of unprecedented
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dissecting RNA structure ensembles in living cells. Particularly, you will: Develop novel methods (both wet and computational) for the accurate interrogation of RNA 2D and 3D structures in living cells. Apply
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between these important climate subsystems, using models of different complexity and a combination of mathematical, numerical and data analysis methods. You can find the other vacancy at PhD Position in
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develop innovative methods to measure diverse isotope dimensions for methane, as well as organic precursors, in order to trace carbon flow in methane-related ecosystems; 2) You will conduct culture