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to develop an aeromedical dispatch management software as a technology hub that provides data-driven prediction model and an automated dynamic decision model. The successful candidate will be responsible
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physics-integrated machine learning models—to predict, analyze, engineer, and understand microbial community dynamics. Applications span precision medicine and built environment microbiomes, with a strong
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. The post holder will have the opportunity to be involved in cutting-edge bespoke neuroimaging technology [3T/7TfMRI-EEG fusion] and advanced data analytics to uncover and predict patterns in large multimodal
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captured from UAVs. The research will address the design of AI models capable of combining heterogeneous sensor modalities, including RGB, thermal, LiDAR, acoustic arrays, GPR, and X-ray backscatter
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Natural History. The researcher will develop deep learning models to predict individual bee age based on wing morphology. This model will be trained of existing wing images and applied to images of museum
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Computational modelling of two-dimensional graphene-based materials School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Natalia Martsinovich Application Deadline
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Institut de Recherche en Génie Civil et Mécanique (GeM) | Saint Nazaire, Pays de la Loire | France | 22 days ago
or random fields or, propagated through the predictive models to improve their robustness. The measurements may also be compared with other mechanical characterisation techniques, including in situ approaches
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SyMulDaM project involving the development of predictive models to quantify the integrity and durability of a nuclear power plant containment structure., within the mechanical engineering department
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observational data, and the application of advanced methods for longitudinal and prediction modelling. You will also conduct methodological research on Bayesian methods and other innovative methodology
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inviting dynamic young scientists, capable of theoretical fracture mechanics and related modeling techniques, to join our team to probe cutting edge issues in fatigue and fracture. Some examples of research