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are being strengthened. Subject and project description This project is focused on the development of high-fidelity reacting flow models to investigate thermal runaway in battery cells, pack, modules, and
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, have enabled the creation of proteins with near-atomic accuracy. Models such as RFdiffusion, LigandMPNN, and hallucination-based frameworks can now generate symmetric oligomers, cages, and backbones
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of proteins with near-atomic accuracy. Models such as RFdiffusion, LigandMPNN, and hallucination-based frameworks can now generate symmetric oligomers, cages, and backbones while optimizing sequence properties
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genetic analyses and generalised linear mixed-effects models, and ideally also in the use of some mathematical models (e.g. Integral Projection Models) Experience in data processing, statistical analysis
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diabetes genetics and genomics. The methodological research may include but is not limited to statistical models using genetic data from family-based studies as well as -omics data for integrative
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. Teaching skills. Additional assessment criteria: Experience with research on stress signalling, metabolomics and phosphorylation cascades Experience with model crops, but also agriculturally relevant plant
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merited. Knowledge of energy markets Experience in research related to district heating and sector coupling Experience in energy system modelling Teaching experience Consideration will also be given to how
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- and 1/f noise characterization of devices. Data analysis and interpretation. Device modelling in collaboration with international partners. Teaching at undergraduate, advanced and postgraduate levels
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, development and inclusive participation for all of our diverse members. We are looking for a driven postdoctoral fellow to work with advanced 3D models of lung to understand regenerative processes in normal
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the design and optimization of various types of turbomachinery. The design and optimization process involve developing models for the components of both axial and radial turbomachines. A strong background in