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to train an AI model that predicts the cis-regulatory code for synthetic genomes (i.e. for cell-free gene expression systems) and correlates the experimental conditions within the synthetic cell
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complex urban settings. Together with researchers from the fields of energy modelling, social network analysis and governance, you will develop new spatial energy concepts to integrate the social
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models at various levels (subcellular, cell-level, organ-level). At the subcellular level, you will develop models of protein interactions using ordinary differential equations. In a second step, these can
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As urban populations grow and energy demands rise, urban-scale energy system modelling is critical for reducing emissions, enhancing resilience, and integrating high shares of renewable energy
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of the mechanical properties of cell walls based on experiments and small-scale simulations developed elsewhere in theGreenTE consortium. Correct and improve your mathematical models in close collaboration with
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PhD on Coupled Subsurface Processes in Mine Water Thermal Energy Storage Faculty: Faculty of Geosciences Department: Department of Earth Sciences Hours per week: 36 to 40 Application deadline
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energy system modelling is critical for reducing emissions, enhancing resilience, and integrating high shares of renewable energy sources. Such modelling provides essential tools for designing low-carbon
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and physics, electrochemistry, nanopores, energy devices, fuel cells, osmotic energy, membrane chemistry and physics, organic chemistry The research project For a successful energy transition wherein
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early steps in lung tumor development. You will use cutting-edge techniques including lung organoid models, single-cell transcriptomics and epigenomics, and CRISPR-based genetic perturbation. Key
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Apply now The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) are looking for: PhD Candidate, Reinforcement Learning for Sustainable Energy This position is embedded