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energy piles have been extensively studied, using field tests, physical modelling, and numerical modelling, the behaviour of energy piles under complex thermomechanical loading (e.g. vertical-horizontal
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postdoctoral position is available in the laboratory of Prof. Alex Persat (EPFL School of Life Sciences, https://www.p-lab.science/ ) to establish a new image-based drug screening platform targeting gram
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for: Analysis of bulk and single cell RNA-sequencing, spatial transcriptomics, and proteomics datasets Integration of experimental model data with public and clinical datasets Statistical modeling and survival
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biology, molecular biology and animal models to investigate how these hybrid cells favour carcinogenesis. Where to apply Website https://app.smartsheet.au/b/form/019eedeef91978fdbc2b67718479eac6?project_id
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related analyses. Below are the potential research topics to be conducted by the researcher: Modeling of energy systems adopting hydrogen and ammonia, and their supply chains Proposal and evaluation
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minerals; energy efficiency; renewable energy technologies; and sustainable fuels. Within this framework, a faculty position in AI-Enabled Modeling and Optimization of Energy Systems is available in
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. This includes large-scale computational mechanics of energy structures, data-driven mechanics, reduced-order modeling, structural optimization, life-cycle analysis, multiphysics modeling of energy materials, and
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muscle cells remains largely unknown. Using human vascular cell models, the student will investigate whether loss of endothelial PKD1 alters smooth muscle cell behaviour, including changes in cell
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chemistry, theory and modelling, fundamental materials physics, and device development, with applications in energy, printed electronics, photonics, and bioelectronics. A strong common theme is materials
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learning, epigenomic data, and mechanistic modelling. The mission is to contribute to the development of predictive models of the replication initiation probability landscape (IPLS) from limited experimental