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–) - this project aims to use small synthetic models of these redox-active cofactors to drive multi-electron redox reactions inside new metal–organic frameworks. Research Group The McPherson group design new metal
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alterations that relate to CHI and principally evaluate their fit as biomarkers for CHI diagnostics. This project will provide training in gene editing, iPSC technologies, and complex cell models with a focus
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developmental incompetence and importantly, fertilised mutant oocytes generate abnormal single-pronucleus zygotes, a phenotype we recently showed is likely conserved in human. Thus, our animal model provides
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development (such as 3D modelling, VR, animation or interactive design) with inclusive design and accessibility. This project bridges computer science and social care to deliver a digital health training tool
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environmental health economics ; economic behaviour, incentives and preferences in health ; and, economic modelling of health policies and technologies . The Opportunity This PhD offers the opportunity to work
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models remain limited to the world of standard dynamic range (SDR). This project seeks to bridge that divide, unifying methods and technologies designed for both SDR and HDR content-spanning still images
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
results. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? You will model the mechanical properties and plastic deformation of materials with diverse
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along with physiological and behavioural data of test drivers and build explainable predictive models out of it. The research team spams Luxembourg, Europe and the USA and will make use of world-leading
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of elements) of the model.; 3) develop an optimization algorithm based on genetic algorithms and metamodels and 4) design functionally graded OC scaffolds using different biomaterials. The doctoral candidate
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? Then check out the vacancy below and apply for a PhD position in this exciting research direction. Join Us! Modern deep learning is progressing fast. Yet even the most advanced neural networks are paired